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Workshop Reports
Reports on the 2016
IJCAI Workshop Series
Edited by Biplav Srivastava, Gita Sukthankar
n This report summarizes the 39 work- he IJCAI 2016 Workshop Program was held in New
shops held as part of the 2016 Interna-
tional Joint Conference on Artificial
Intelligence, held in New York from July
9–11.
T York, New York, from July 9–11. It included 27 full-day
and 12 half-day workshops covering a broad range of
topics. Some workshops focused on recent improvements in
computational frameworks such as statistical relational mod-
els and algorithmic game theory. The two deep learning
workshops in particular generated a great deal of excitement
with more than 200 attendees combined. However the
majority of workshops centered on application areas includ-
ing multiagent systems, natural language processing, cogni-
tive computing, and social media analysis. The usage of arti-
ficial intelligence within the biological and health sciences
was viewed as an important theme, and there were four
workshops in that area. In addition to the specialized work-
shops, there was a workshop on ethics in artificial intelli-
gence, a broad area of concern for most artificial intelligence
researchers. Although most of the workshops were either
completely new or had only been offered for a few years, one
workshop (Qualitative Reasoning) celebrated its 29th year.
Summaries of the workshops were presented at two evening
sessions during the main conference for the benefit of atten-
dees who could not attend the workshop days and are also
posted online.1
94 AI MAGAZINE Copyright © 2016, Association for the Advancement of Artificial Intelligence. All rights reserved. ISSN 0738-4602Workshop Reports
Bridging the Gap Between Human tory), Daniel Borrajo (Universidad Carlos III),
Michael T. Cox (Wright State University), and Neil
and Automated Reasoning Yorke-Smith (American University of Beirut).
Human reasoning or the psychology of deduction is Participants discussed new formal models of goal
well researched in cognitive science. Automated reasoning, recognition, and representation; and
deduction, on the other hand mainly focuses on the explored the relationships with MDPs, automated
automated proof search in logical calculi. This work- planning, and HCI. Applications included a goal-rea-
shop offered a platform for approaches coupling soning algorithm operational in a $100,000 UUV
these two areas. The program covered the following test. David Aha (NRL) and Sebastian Sardina (RMIT)
themes: spatial cognition, theorem proving, and nat- gave invited talks.
ural games; logic programming approaches to model Two of the major outcomes of the workshop were
human reasoning; syllogistic reasoning; computa- to challenge the assumption of static, user-provided
tional models for human reasoning; benchmarks for goals, and to highlight the connection with BDI
commonsense reasoning; argumentation; automa- agent systems. After further revision and review,
tion of human inference. selected papers will appear in AI Communications.
During active exchange, it was remarked that even
though the number of theories that claim to explain
parts of human reasoning is strongly increasing, only
Social Influence Analysis
few comparisons on common data sets do exist. The Second International Workshop on Social Influ-
Therefore, it was proposed that the field of human ence Analysis (SocInf2016) featured the presentation
reasoning would greatly benefit from benchmarks of peer-reviewed accepted papers in which diverse
and competitions similar to the ones in automated social networks such as Twitter and Pinterest, hyper-
theorem proving. Benchmarks and a first competition graphs, and even small groups (business meetings,
are planned for the next Bridging the Gap Between group discussion) were used as case studies. Addition-
Human and Automated Reasoning workshop. ally, SocInf2016 included two invited keynotes: Big
The second Bridging the Gap Between Human and Network Analysis — Algorithms and Applications (by
Automated Reasoning workshop was organized by Jie Tang) and Negative Social Influence in Online Dis-
Ulrich Furbach, Steffen Hölldobler, Marco Ragni, and cussions (by Justin Cheng). These invited talks gener-
Natarajan Shankar. ated a great deal of audience interest. The workshop
also hosted a contest sponsored by Alibaba Tianchi
named “Brick-and-Mortar Store Recommendation
Computer Games Workshop with Budget Constraints” with $10,000 in prizes.
More than 30 attendees came together to interact The major outcomes of the workshop included the
about the advancements of AI in game-playing pro- identification of different research gaps in the field
grams at the fifth Computer Games workshop. There and discussion of possible approaches to different
were 11 presentations about different AI techniques aspects of social influence analysis.
and a variety of games. The games addressed were The workshop was organized by Marcelo Armen-
Breakthrough, Space Navigator, Same Game, One tano, Ariel Monteserin, Jie Tang, and Virginia Yanni-
Night Ultimate Werewolf, General Game Playing, belli.
Atari games, Go, and Hex. The AI techniques includ-
ed Monte Carlo tree search (MCTS), alpha-beta, nest-
ed rollout policy adaptation, deep learning, rein-
Ethics for Artificial Intelligence
forcement learning, and natural language classifier. The Ethics for AI workshop featured the presentation
The most popular algorithms were MCTS and Deep of accepted peer-reviewed papers on a diverse set of
Learning. The organizers plan to continue next year topics concerning ethical and legal issues in artificial
with a sixth Computer Games workshop. intelligence. Its aim was bringing together approach-
The workshop was organized by Tristan Cazenave, es from many disciplines and diverse points of view
Mark H. M. Winands, and Stefan Edelkamp. and fostering discussion to clarify questions and
cooperative debate in finding ways forward. The dis-
ciplines of computer science, law, philosophy, eco-
Goal Reasoning nomics, and social sciences were represented. Includ-
Goals are a unifying structure across the variety of ed were empirical approaches, for example, lab work
intelligent systems, serving in the management of furthering understanding of the ethical import of
long-term behavior, anticipating the future, selecting concepts such as “transparency”; as well as more the-
among priorities, committing to action, generating oretical work, such as work examining the relation-
expectations, assessing trade-offs, resolving the ship between ethical frameworks, law, and AI, how
events, and learning from experience. The workshop moral decisions are made, how best to think about
on Goal Reasoning, the fourth in a series, was organ- central issues such as “autonomy.”
ized by Mark “Mak” Roberts (Naval Research Labora- The workshop considered immediate concrete
WINTER 2016 95Workshop Reports
issues in AI such as models for developing the regula- parency, the influence of interaction modalities and
tion of autonomous vehicles, creating norms for the the need to ask good questions for efficient learning.
regulation of autonomous trading agents, as well as In future workshops, we hope to explore these ideas
more speculative future projections of AI, the issue of in greater detail as well as have better integration
superintelligence, its likelihood, and ethical import. with the cognitive science and human-computer
The opinion was voiced that progress on these com- interaction community.
plex and important problems is being made. The workshop was organized by Kaushik Subra-
The workshop was organized by Michael manian, Heni Ben Amor, Charles Isbell, and Andrea
Wooldridge, Peter Millican, Christopher Megone, Thomaz.
and Paula Boddington.
Advances in Preference
Computational Models of Handling
Natural Argument The 10th Multidisciplinary Workshop on Advances
In its 16th year, the Computational Models of Natu- in Preference Handling, which brought together
ral Argument workshop series2 serves the argument researchers from numerous subfields who are inter-
and computation research community with a focus ested in computational aspects of preference han-
on natural argumentation, where naturalness may dling, aims at discussing novel and emerging
include expression in text, multimedia, or graphics; research on preferences, and provides an opportuni-
use of rhetorical devices; or taking into account char- ty for cross-fertilization between fields. The program
acteristics of the audience such as affect. A distinctive comprised 11 technical presentations and an invited
feature of the workshop is its aim to reach different talk by Vincent Conitzer on “Mechanism Design in
communities and perspectives. It has been colocated Data-Rich Environments.” The papers are available
throughout the years with generalist AI conferences on the workshop website.3
as well as more specialized meetings on multiagent Preferences are a central concept of decision mak-
systems, user modeling, and legal informatics. ing and are used in fields such as AI, databases, and
The 2016 workshop featured a keynote talk and human-computer interaction. Preference-based sys-
presentations of six papers and two research abstracts. tems do not return arbitrary responses, but choose
Topics included models of argumentation for decision results that respect users’ preferences. Embedding
making, political analysis, and intelligence analysis; morality when handling preferences and dealing
models of biomedical argumentation in research jour- with the potential and risks of big data were identi-
nals and popular media; annotation of rhetorical fig- fied as challenging endeavors for the future.
ures; and unique characteristics of argumentation in The workshop was organized by Markus Endres,
social media and in face-to-face dialogue. Nicholas Mattei, and Andreas Pfandler.
The workshop was organized by Floris Bex, Flori-
ana Grasso, and Nancy Green.
Biomedical Informatics
with Optimization and
Interactive Machine Learning:
Machine Learning
Connecting Humans
The Biomedical Informatics with Optimization and
and Machines Machine Learning workshop attracted a total of 25
The Interactive Machine Learning workshop focused submissions (full paper and short abstract tracks
on the design and analysis of algorithms that facili- combined), that went through a peer-review process.
tate machine learning with the help of human inter- Fifteen were accepted for oral or spotlight/poster pre-
action. During the workshop, 13 papers were pre- sentations. Five keynote speakers from diverse back-
sented covering a variety of topics such as grounds were invited, and more than 40 people
human-machine teaching strategies, collaborative attended the workshop. Best paper awards were cho-
robot learning, topic models, and systems operations. sen, with sponsorship by Microsoft Research. The
There were four invited talks selected to span the workshop catalyzed synergies among biomedical
breadth of research in this field, including presenta- informatics, machine learning, and optimization.
tions on reinforcement learning from users, active The workshop meets the compelling demand for
learning, cognitive science, and interactive robotics. novel machine learning, data mining, and optimiza-
A highlight of the workshop was a lively panel dis- tion algorithms to specifically tackle the unique chal-
cussion on the realities of interactive machine learn- lenges associated with biomedical and health-care
ing, which focused on the real-world challenges of data. By reviewing and discussing the recent major
autonomous and interactive learning systems. breakthroughs in machine learning and optimiza-
Some of the important talking points from the tion, it fosters idea exchanges among applied mathe-
workshop included the importance of model trans- maticians, computer scientists, bioinformaticians,
96 AI MAGAZINEWorkshop Reports
computational biologists, industrial engineers, clini- Contributed talks covered a diverse range of AI tech-
cians, and health-care researchers. niques applied to synthetic biology topics.
The workshop was organized by Zhangyang Wang, Synthetic biology is a rich domain for AI with
Yang Shen, Shuai Huang, and Jiayu Zhou. many places for AI to make an impact. We hope this
is the first of many workshops on this topic at AI ven-
ues that help develop collaborations between the two
Language Sense communities. The workshop was organized by Fusun
on Computers Yaman, Aaron Adler, and June Medford.
The second Language Sense on Computers workshop
was convened with the aim of gathering NLP spe- Artificial Intelligence for
cialists and linguists who work on the interesting
phenomena and unsolved problems of language.
Knowledge Management
The workshop featured 13 presentations, which The workshop covered various facets of knowledge
covered various topics including narratology and management such as ontologies applied to access
plot recognition, expressions for describing taste, complex data in bioimaging or to local self-govern-
word ordering tendencies, and approaches to ment, conceptual navigation and e-learning systems
metaphor processing. There were also papers orient- that use polyadic formal concepts, automatic selec-
ed toward practical applications: one about recog- tion of talents for collaborative new product design,
nizing Cockney rhyming for cyberbullying detec- self-organizing maps applied to RFM analysis in the
tion, one on automatic common sense ontology packaging industry, selection of software for business
expansion, and one that introduced improved meth- intelligence, platforms for city dwellers, AI enhanc-
ods for affect recognition in dialogues. Two presen- ing intelligent use of energy, segmentation of social
tations were related to elderly-care solutions. networks, and semantic reasoning in knowledge
Researchers from Japan presented work on analyzing management systems.
a daily task (shopping) and considered the role of The invited talk was devoted to learning ontologies
communication bots in therapy. Two papers for medical data. Janusz Wojtusiak, associate profes-
addressed and tried to answer the following sor of health informatics at George Mason Universi-
exploratory challenge problems: “Can computers ty, Fairfax, recalled various machine-learning tech-
write poetry?” and “Can computers predict the niques and highlighted the importance of knowledge
future?” The conclusion of the workshop was that and context for deep exploring of medical data.
difficult problems, although still being very hard to The proceedings of the workshop are available
solve, show the weakest points of current natural online.4 Selected, extended papers from this work-
language processing. We agreed that the challenges shop will be published by Springer in the Advances in
are definitely worth taking. Information and Communication Technology series.
The workshop was organized by Akinori Abe and The workshop was organized by Eunika Mercier-Lau-
Rafal Rzepka. rent, Mieczyslaw Owoc, and Gulgun Kayakutlu.
AI for Synthetic Biology Knowledge Discovery in
Synthetic biology is the systematic design and engi- Health-Care Data
neering of biological systems; it holds the potential
for revolutionary advances, for example, in medicine The goal of the Knowledge Discovery in Health-Care
and environmental remediation. Unfortunately this workshop was to foster discussion and present
potential is unreachable with the current practice of progress on research efforts that leverage large
designing novel organisms at the DNA level, which is amounts of observational data (clinical, biological,
similar to programming in assembly code. Synthetic physiological) to expedite discovery in medicine. The
biology has reached a complexity barrier that AI can workshop was intended to encourage a cross-discipli-
help to overcome, just like it did with programming nary exchange of ideas between medical researchers
languages that allow computer scientists to think and and the artificial intelligence community. Artificial
operate at higher abstraction levels while automating intelligence and machine-learning approaches hold
the translation to bits. the potential to reveal not readily apparent, hidden
The AI for Synthetic Biology workshop aimed to information in biological and medical health-care
cross-pollinate the two research fields. Thanks to the data sets. The results of such discoveries can aid the
Bio-Design Automation Consortium and Raytheon development of novel diagnostic and prognostic
BBN Technologies, the workshop provided funds to tests, inform descriptive, predictive, and prescriptive
support synthetic biologists’ travel to ensure diversi- analytics, and guide hypothesis generation.
ty of the audience. Invited talks introduced synthet- One of the highlights of the workshop was five
ic biology to AI researchers and highlighted areas world-renowned keynote speakers delivering four
where AI addresses synthetic biology challenges. invited talks. The workshop also featured six paper
WINTER 2016 97Workshop Reports
presentations and five posters that were accepted ment learning for robotics and explainable AI.
after the peer-review process. Participants were from The papers focused on a variety of analysis (for
Slovenia, United States, United Kingdom, and Japan. example, classification) and synthesis tasks (for
The workshop was organized by Marzieh Nabi, example, design). They also varied by application cat-
Jonathan Rubin, Ali Shojaie, Ary L. Goldberger, egory (for example, natural language understanding,
Madalena Damásio da Costa, and Daniel G. Bobrow. agent control, decision aids) and by their use of
trained neural networks to assist with specific rea-
soning tasks (for example, solving Winograd
Agent-Mediated Electronic schemas, goal selection, game move selection, object
Commerce and Trading Agents prediction, activity recognition, customer churn pre-
Design and Analysis diction). In summary, this workshop provided a
forum for exploring how deep learning methods
The International Workshop on Agent-Mediated might interact and inform AI processes.
Electronic Commerce and Trading Agents Design and The workshop was organized by David W. Aha, Yian-
Analysis5 was organized into two sections, one dedi- nis Aloimonos, Andrew S. Gordon, and Alan Wagner.
cated to auctions, mechanism design, and Walrasian
equilibria; while the other was focused on problems
related to power TAC. Following tradition, the work- Knowledge-Based Techniques
shop was associated with the Trading Agent Compe- for Problem Solving and
tition (TAC) and hosted the award ceremony for the
two TAC 2016 tracks: Power and Ad Exchange TAC. Reasoning
Mariano Schain, senior software engineer at
Google, gave a fascinating talk on the TAC Ad The Knowledge-Based Techniques for Problem Solving
Exchange Game. The workshop was organized by and Reasoning workshop attempted to bridge the gap
Sofia Ceppi, Chen Hajaj, Valentin Robu, Ioannis A. between knowledge representation communities
Vetsikas, and Esther David. (focusing on expressivity and semantics of models)
and problem solving communities (focusing on effi-
General Game Playing cient problem solving). It was inspired by area-specific
workshops such as Knowledge Engineering for Plan-
AI researchers have for decades built game-playing ning and Scheduling and Constraint Modeling and
agents capable of matching wits with the strongest Reformulation and the now discontinued Symposium
humans in the world in board games like Chess and on Abstraction, Reformulation, and Approximation.
Go and video games such as StarCraft and Pac-Man. The full-day workshop featured presentations of 10
Research into general game playing takes this to the peer-reviewed papers and an invited talk “The Mod-
next level: to build intelligent software agents that eling Beauty of Constraint Solving” given by Veroni-
can, given the rules of any game, automatically learn ca Dahl. All papers are available through CEUR Work-
a strategy for playing that game at an expert level shop Proceedings. The topics of presentations varied
without human intervention. from natural language processing over diagnosis and
Results discussed and achieved at the Fifth Inter- robotics up to search and planning. The papers
national General Game Playing workshop included showed the importance of problem modeling for effi-
boosting the efficiency of reasoning about game cient problem solving and confirmed the existing gap
rules, general game playing with imperfect informa- between the communities. Hence similar events in
tion, Monte Carlo tree search, and general video future seem desirable as a communication platform
game playing. Selected papers from this workshop in particular at general AI conferences, where the
and the Computer Games workshop will be jointly knowledge representation and problem solving com-
published by Springer. munities naturally meet.
The workshop was organized by Stephan Schiffel, The workshop was organized by Roman Barták,
Julian Togelius, and Michael Thielscher. Lee McCluskey, and Enrico Pontelli.
Deep Learning for Multiagent Path Finding
Artificial Intelligence The Second International Workshop on Multiagent
The Deep Learning for Artificial Intelligence work- Path Finding focused on recent advances in multia-
shop featured the presentation of peer-reviewed gent path finding, particularly in the domain of opti-
papers that focused on integrating deep learning (DL) mal and near optimal methods.
with AI techniques (for example, for tasks involving Participants presented several new approaches to
the use of symbolic representations and related infer- multiagent path finding, including using ad hoc
ence methods). Additionally, two invited speakers group formation to ease reactive navigation for large
presented on DLAI-related topics: deep reinforce- groups of agents, any-angle planning for multiagent
98 AI MAGAZINEWorkshop Reports
systems, and structuring the environment to make approaches ranging from incorporating structured
planning easier. Invited speakers gave reviews of the KB’s into machine learning to exploiting deep learn-
state of the field. ing for extracting domain semantics. We identified
The conclusion of a group discussion was that key research priorities for the future as: knowledge
there are a large number of known algorithms, but representation with evolution, and machine learning
our understanding of their benefits and drawbacks is with explanation. The workshop proceedings, pres-
insufficient. The participants committed to produc- entation slides, and video recordings are available
ing a good set of standard benchmarks to aid com- online.6
parisons between approaches. The workshop was organized by Rajaraman Kana-
The workshop was organized by Howie Choset, gasabai, Ahsan Morshed, and Hemant Purohit.
Sven Koenig, and Glenn Wagner.
Natural Language Processing
Computational Modeling Meets Journalism
of Attitudes and Natural language processing has matured over the
Sentiment Analysis years to the point where a suite of technologies is
available to cope with many problems raised by the
The combined workshops on Computational Model-
contemporary need of global information. Conse-
ing of Attitudes and Sentiment Analysis where AI
quently, it is now time for NLP to become engaged as
Meets Psychology focused on the intersection
an active partner for both journalists and readers.
between sentiment analysis and psychology and rep-
The Natural Language Processing Meets Journalism
resented experts in both the psychological and cog-
workshop attracted the interest of researchers both in
nitive sciences along with experts in computer sci-
computational linguistics and journalism and of pro-
ence. Collectively, the papers illustrated the varied
fessionals in the news production system. The pri-
approaches to understanding sentiment and atti-
mary goal was to have a forum in which it would be
tudes in real human data, to include theoretic mod-
possible to share and discuss advancements in natu-
els of human information processing and advanced
ral language processing and real needs in the field of
machine-learning approaches for complex feature
journalism. At this workshop there were papers that
extraction of human-generated data. The types of
presented technologies that go deep into the sub-
human-generated data ranged from text to speech
stance of a piece of news, as a savvy journalist or an
and audiovisual data. The keynote speakers repre-
alert reader will do.
sented world-renowned researchers from machine
The workshop was organized by Octavian Popescu,
learning (Björn W. Schuller) and social psychology
Carlo Strapparava, and Larry Birnbaum.
(Russell Fazio). The final round-table discussion
brought novel insights to both the psychological and
the computer science participants and a sense that Advances in Bioinformatics and
there was room for further cross-fertilization to Artificial Intelligence:
understand human behavior and to provide more
sophisticated machine-learning applications. Bridging the Gap
The two workshops were organized by Sivaji Bandy- This one-day workshop brought together scholars and
opadhyay, Erik Cambria, Dipankar Das, Braja Gopal practitioners active in AI-driven bioinformatics, to
Patra, Kiran Lakkaraju, Mark Orr, and Samarth Swarup. present and discuss their research, share their knowl-
edge and experiences, and discuss the current state of
Semantic Machine Learning the art and the future improvements to advance the
intelligent practice of computational biology.
The 2016 Semantic Machine Learning workshop The 2016 program comprised one keynote speaker,
focused on the latest advances and research chal- two invited speakers and seven paper presentations.
lenges in fusing data and functional and domain The details are accessible online.7 The presentation
semantics with traditional machine learning toward topics were divided into two areas: biology-inspired
enhancing its performance. The workshop featured computation and computation providing new
two invited keynotes, four paper presentations, and insight into biology. The workshop covered the broad
a panel discussion that were well received. The scope of AI and bioinformatics, including machine
keynotes highlighted the importance of unsuper- learning, knowledge representation, natural language
vised learning and illustrated diverse ways to formal- processing, web mining, comparative genomics, sys-
ize and incorporate domain semantics into it, while tem biology, and networks.
the panel on challenges and potential directions to There is a plan for for a future workshop to discuss
improve machine learning with semantics facilitated personalized medicine. The workshop was organized
diverse perspectives on semantic machine learning. by Abdoulaye Baniré Diallo, Engelbert Mephu
The new results from papers demonstrated Nguifo, and Mohamed Zaki.
WINTER 2016 99Workshop Reports
Algorithmic Game Theory research challenges in deep RL. There was significant
interest from the audience and several expressed the
The workshop on Algorithmic Game Theory featured hope that this will continue next year as well.
the presentation of 11 technical papers in various top- The workshop was organized by Sarath Chandar,
ics of algorithmic game theory (mainly networks and Sridhar Mahadevan, Balaraman Ravindran, and Ger-
social choice). In addition, there were an hour-long ald Tesauro.
invited talk by David Parkes and a short rump session
for advertising AGT-related papers in the main IJCAI
session. The workshop brought together AI Natural Language Processing
researchers that are interested in strategy and game for Social Media
theory, but from different perspectives: using compu-
tational techniques to games, efficiently computing The goal of the research discussed at the Fourth
and implementing solution concepts, and exploring International Workshop on Natural Language Pro-
alternative notions of individual and social utility. cessing for Social Media was to enhance social com-
The workshop was organized by Georgios Chalki- puting with AI and natural language processing
adakis, Nicola Gatti, Reshef Meir, and Carmine Ventre. (NLP). Presentations focused on NLP problems using
information extracted or learned from social net-
works and social media. New research problems
Statistical Relational AI related to both social computing and NLP were high-
lighted during the workshop.
The purpose of the Sixth International Workshop on
The workshop was organized into four parts. First,
Statistical Relational AI workshop series is to bring
Yuheng Hu (University of Illinois at Chicago) deliv-
together researchers and practitioners from two
ered an excellent keynote speech on event analysis
fields: logical (or relational) AI and probabilistic (or
in social media. His talk received great feedback and
statistical) AI. Until recently, research in them has
brought lively discussions among the participants on
progressed independently with little or no interac-
the insights of people’s engagement with events and
tion. The workshops instead provide a big picture
the tweeting behaviors during engaged events. Sec-
view on AI. It is the study and design of intelligent
ond, sentiment analysis using AI, especially
agents that act in noisy worlds composed of objects
machine-learning techniques, was one of the key
and relations among the objects.
workshop topics. Third, deep learning was men-
The 2016 workshop featured three invited talks, by
tioned by every presentation. Fourth, due to the
William Cohen, on “TensorLog: A Differentiable
importance of benchmark datasets, SocialNLP
Deductive Database,” by Daniel Lowd, on “Adversar-
encouraged data papers to share resource and data
ial Statistical Relational AI,” and by Percy Liang, on
creation and preliminary analysis. Two interesting
“Querying Unnormalized and Incomplete Knowl-
data track papers were accepted this year, one on
edge Bases.” The workshop had 25 accepted papers,
Hindi-English Mixing, and another on Moroccan
which were presented as spotlight talks and posters.
Arabic code switching. The organizers have main-
The workshop details are available online.8
tained a modest size with 6 full paper presentations
The workshop was organized by Guy Van den
and a total of 20 to 25 participants.
Broeck, Mathias Niepert, Sebastian Riedel, and David
The workshop was organized by Jane Yung-jen
Poole.
Hsu, Lun-Wei Ku, and Cheng-Te Li.
Deep Reinforcement Learning: Qualitative Reasoning
Frontiers and Challenges
Qualitative Reasoning workshops discuss research on
Deep learning and reinforcement learning are among automated understanding of the world derived from
the most promising machine-learning methods incomplete, imprecise, or uncertain data, realized as
today. This workshop focused on applications of deep cognitive systems capable of knowledge-level inter-
learning for representation learning in reinforcement action (with humans in the loop).
learning and applications of reinforcement learning This year’s workshop hosted an inspiring invited
for more efficient deep learning. The primary motiva- talk by Diedrich Wolter on qualitative spatial reason-
tion of organizing the workshop here was to involve ing, followed by 14 presentations of ongoing re-
the IJCAI community in this research drive. search. The presentations focused on topics includ-
The workshop featured seven keynote talks by lead- ing conceptual modeling and simulation for
ing researchers in the field: Pieter Abbeel, Remi education (learning); diagnosis and decision making
Munos, Joelle Pineau, Doina Precup, David Silver, (for example, environmental problems); explanatory
Satinder Singh, and Peter Stone. Speakers covered var- models for health, biodegradation, and science;
ious topics including deep RL for games, NLP, robot- order-of-magnitude reasoning (for business and mar-
ics, and RL for deep learning. The workshop also fea- keting); human and (physical) robot interaction dur-
tured 10 contributed papers and a panel discussion on ing gaming; and, of course, qualitative spatial rea-
100 AI MAGAZINEWorkshop Reports
soning,. All contributions can be found unknown. It featured the presentation Closing the Cognitive
on the website of the workshop..9 of peer-reviewed papers that focused
A key observation throughout the on different sorts of mixed agent type Loop for Human-Aware AI
workshop was that contemporary interactions. It was composed of two The Third Closing the Cognitive Loop
challenges typically concern multidi- sections, one dedicated to modeling for Human-Aware AI workshop fea-
mensional problems, which require the strategic reasoning of the oppo- tured the presentation of accepted
semantic interoperability of miscella- nents under different circumstances papers that went through a peer-
neous representations and algorithms. and the other dedicated to planning review process and focused on success-
The workshop was organized by Bert and optimization in mixed agent type ful addressing of human-in-the-loop
Bredeweg, Kamal Kansou, and settings. issues. Additionally, two invited speak-
Matthew Klenk. In conclusion, a growing number of ers presented deployed applications of
investigations consider a variety of AI that interact closely with humans —
interacting agents. However, much cognitive assistance for data scientists,
Cognitive Knowledge effort is still needed to close the gap and intelligent control of crowdsourc-
Acquisition between the state of the art and het- ing applications.
and Applications erogeneous multiagent systems. With One of the major outcomes of the
this in mind, the community still workshop was the realization that each
Motivated by the goal of developing needs to assemble diverse perspectives AI system that was presented in the
cognitive systems that learn, reason, to promote a robust understanding of workshop featured a unique set of
and interact naturally with humans, agent mix. interaction challenges that needed to
the Cognitive Knowledge Acquisition The workshop was organized by
and Applications workshop series10 be overcome in order to make those
Enrique Munoz de Cote, Long Tran- systems human aware. This sparked a
offers an informal setting that pro- Thanh, Christopher Amato, and
motes lively discussion on work that discussion on the major problem pil-
Prashant Doshi. lars for human-aware AI, which
bridges cognitive psychology and arti-
ficial intelligence. Emphasis is placed include topics such as explanation of
on developing knowledge representa- Ontologies and Logic decisions; interpretability of the deci-
tions and acquisition processes that sion process; efficient and time-sensi-
Programming for tive context transfer; division of skills
allow a cognitive system to explain the
inferences that it draws, while also Query Answering and labor; and legal and ethical issues.
being able to accommodate user feed- The next iteration of the workshop will
The Ontologies and Logic Program-
back to adapt and improve its work- focus more specifically on these prob-
ming for Query Answering workshop
ings. lem pillars for human-aware AI.
featured the presentation of accepted
The workshop featured a keynote The workshop was organized by Kar-
papers that underwent a peer-review
talk by Ernest Davis on building a cor- tik Talamadupula, Shirin Sohrabi, and
process. Some papers addressed query
pus of texts tagged with commonsense Murray Campbell.
answering while taking ontologies into
inferences and contributed talks on account with new results on temporal
learning knowledge for commonsense
Notes
OBDA and on a unified framework for
psychology, on robots learning to 1. bit.ly/2atCpD9.
inconsistency-tolerant query answer-
ground text on their visual inputs, on 2. cmna.info.
ing; other papers were devoted to non-
recommending films while explaining monotonic reasoning, inconsistency 3. www.mpref-2016.preflib.org.
why, on using Minsky’s critic networks handling and expressing default nega- 4. ifipgroup.com/AI4KMProceedings2016.
for common sense, on enhancing tion in ontologies with new results on pdf.
expert-developed taxonomies, and on mapping data to ontologies using exis- 5. www.sofiaceppi.com/AMECTADA2016.
achieving more flexibility than static tential ASP, on qualitative disjunctive 6. datam.i2r.a-star.edu.sg/sml16.
dictionaries through learning. logic programs for ontology mapping, 7. bioinfo.uqam.ca/IJCAI_BAI2016.
The workshop was organized by
and on existential ASP for computing 8. www.starai.org.
Loizos Michael and Erik T. Mueller.
repairs. Additionally an invited speak- 9. ivi.fnwi.uva.nl/tcs/QRgroup/qr16/index.
er focused on query rewriting for html.
Interactions with ontology-based query answering. 10. cognitum.ws.
The workshop gave rise to rich dis-
Mixed Agent Types cussions and an open issue emerged:
The Interactions with Mixed Agent how to define fragments of existential Biplav Srivastava is a research staff mem-
Types workshop centered on fostering ASP covering lightweight ontological ber at IBM Thomas J. Watson Research Cen-
ter, USA.
a reach discussion about how to design languages while keeping decidability
intelligent agents capable of interact- and efficiency? Gita Sukthankar is an associate professor at
ing with other agents of different types The workshop was organized by University of Central Florida in Orlando.
and whose objectives, learning dynam- Odile Papini, Salem Benferhat, Laurent
ics, and representation of the world are Garcia, and Marie-Laure Mugnier.
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