SIMBA: an Approach for Real-Time Multi-Agent Systems
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SIMBA: an Approach for Real-Time Multi-Agent
Systems
V. Julian, C. Carrascosa, M. Rebollo, J. Soler and V. Botti
Dept. Sistemes Informàtics i Computació.
Universitat Politècnica de València.
{vinglada,carrasco,mrebollo,jsoler,vbotti}@dsic.upv.es
well-known that a RTS is formed by a set of tasks
Abstract characterised by a deadline, a period, a worst-case
execution time and an assigned priority. A dead-
The use of the agent/multi-agent system paradigm line defines the greatest time interval in which the
has increased sharply as an important field of re- system can provide a response. If the response is
search within the Artificial Intelligence area. In re- obtained after this time, it will probably not be use-
cent times, the application of this paradigm seems ful. Researchers differentiate between two types of
appropriate for solving complex problems which RTS. The first, called Hard Real-Time System, is a
require intelligence and bounded response times. RTS where the execution of a task after its deadline
This paper presents Simba : an architecture based is completely useless. Systems of this kind are criti-
on Artis agents as its main component for the de- cal systems and if timing responses are not satisfied,
velopment of real-time multi-agent systems. The this will result in severe consequences. The second,
Artis agent architecture guarantees an agent re- called Soft Real-Time System, is characterised by
sponse that satisfies all its critical temporal restric- the fact that the execution of a task after its dead-
tions in a real-time environment. The main feature line only decreases the quality of the task result
of Simba systems is their applicability for complex, [16]. Different techniques are needed for hard and
distributed, real-time domains. The architecture soft RTS.
allows the communication among agents taking into On the other hand, a multi-agent system which
account their hard temporal restrictions. involves several agents that collaborate towards the
In order to show the use of systems of this kind, achievement of a joint objective is viewed as a team
the paper describes the design of a multi-agent sys- of agents. Most proposed teamwork structures [10]
tem for the distributed intelligent control of a resi- [3] rely on agents in a multi-agent system to nego-
dential building. tiate and/or contract with each other in order to
initiate team plans. However, in dynamic, real-
Keywords: agents, multi-agent systems, real-time
time domains with limited communication, com-
AI.
plex negotiation protocols may take up too much
time. Therefore, these protocols are not suitable
for time-bounded problems.
1 Introduction
Our work has been focused in time critical en-
Over the last few years, the application of the agent vironments in which the full system can be con-
/ multi-agent paradigm in real-time environments trolled by autonomous agents that need communi-
arises from the required capacities of new real-time cation to improve the system goal. This focus mo-
systems. This paradigm attempts to incorporate tivates the introduction of Social Real-Time Do-
flexibility and distribution in new real-time designs. mains. In such domains, agents need to act au-
A Real-Time System (RTS) is a system in which tonomously while still working towards a common
the correctness of the system depends not only on system goal. Time-critical environments require
the logical result of computation, but also on the real-time response and, therefore, they eliminate
time at which the results are produced [15]. It is the possibility of excessive communication amongagents. • The domain has unreliable communication, ei-
According to these concepts, it is possible to de- ther in terms of transmission reliability or
fine a Real-Time Agent as an agent with temporal bandwidth limits. If an agent ai ∈ A sends
restrictions. These restrictions may be hard, soft or a message m to agent aj ∈ A, then m arrives
both. A real-time agent should guarantee its tem- with some probability; or an agent ai can only
poral restrictions and, concurrently, it should try receive x messages every y time units. That
to accomplish its goals. Finally, if a real-time agent is, sending a message does not guarantee its
is included as a component of a multi-agent sys- reception.
tem, this system can be considered as a Real-Time
Multi-Agent System. It is important to highlight • A message m has a maximum length K, and an
that the agent may have its interactions bounded. agent can send and receive at least one message
This modification will affect all the communication m with a period pi .
processes in the multi-agent system.
In the extreme case, the communication chan-
An architecture for a real-time multi-agent sys-
nel lose all the messages, then an interval of no
tem is presented in this paper. The proposal is
communication will appear, requiring the agents to
called Simba (Multi-Agent System Based on Ar-
act completely isolated. If agent ai cannot carry
tis ) and it constitutes a significant extension of
on with its action until receiving a message from
the Artis agent architecture approach for real-time
aj , then the team’s performance could suffer. Be-
environments [2]. Simba can be seen as a set of
cause of the unreliable communication, the message
Artis agents and their interactions. This proposal
might not get through on the first try. And because
increases the applicability of the Artis agent archi-
of the dynamic, real-time nature of the domain, the
tecture for problems where a multi-agent approach
team’s likelihood or efficiency of achieving G is re-
is more suitable than a centralised one.
duced. However, if a message is received, it will be
The rest of the paper is structured as follows: treated in a finite amount of time.
section 2 focuses on the features of social real-time Intelligent building sensing and control is a social
domains. Section 3 presents an overview of the real-time domain since a set of agent controls differ-
Simba architecture for real-time environments and ent subsystems and they need to communicate with
its main component, the Artis agent. Section 4 each other in order to maintain the global objective
goes into the communicative aspects of this type of [13] [1]. There are several other examples of social
agents. In section 5, an intelligent building manage-
real-time domains, such as port container terminal
ment system is described as an example. Finally, management, factory maintenance, distributed in-
some conclusions are mentioned in section 6. dustrial process control and robot team control.
2 Social Real-Time Domains 3 SIMBA Architecture
We define a social real-time domain as a domain Simba is an architecture for multi-agent systems
with the following characteristics: to work properly in social real-time domains. The
Simba architecture constitutes the natural evolu-
• There is a team of autonomous agents A that tion of the Artis agent architecture, since it allows
collaborate to achieve a common long-term for the development of different related agents for
goal G. hard real-time environments.
Basically, a Simba system is formed by a set of
• Periodically, each agent can read or send mes- Artis agents (AA) with probably hard temporal
sages m with no adverse effects upon the restrictions. This set of agents controls the subsys-
achievement of G. tem of the real-time environment with hard critical
constrains. Additionally, the system may integrate
• The domain is dynamic and time-bounded. different types of agents, which cover other non-
This means that team performance is adversely critical activities on the system. For this reason,
affected if an agent fails to act for a period. Simba must be prepared to incorporate heteroge-
Each agent is able to manage hard real-time neous agents using standard agent-interaction pro-
restrictions and to solve a system subproblem. cesses.As mentioned above, the main component of the munication acts are included into these pro-
Simba architecture is the Artis agent, so, the ar- cesses. So, the Artis agent has a Commu-
chitecture of this special type of agent is presented nication Module (CoMo) which is in charge of
in the following point. Later, the formal approach controlling the sending and arrival of messages.
and design aspects of the Simba architecture are
described. • A set of in-agents (internal agents) that mod-
els the AA behaviours in order to achieve the
AA goals. An in-agent is an internal entity
3.1 The ARTIS Agent Architecture
that has the necessary knowledge to solve a
The Artis architecture is an extension of the black- particular problem (this knowledge can incor-
board model [12] which has been adapted to work porate IA techniques that provide intelligence
in hard real-time environments. This architecture for solving the problem). Basically, this en-
includes the use of well-known techniques of Real tity periodically performs a specific task (which
Time Artificial Intelligence Systems [9]. This ap- may or may not be complex). The main
proach guarantees reacting on the environment in reason for splitting the whole problem-solving
a dynamic and flexible way. It incorporates all the method into smaller entities is to provide
necessary aspects that the agency features provide an abstraction which organises the problem-
to a software system, but adapted to hard real-time solving knowledge in a modular and gradual
environments. way. Depending on the temporal restrictions
The Artis agent architecture guarantees an and the intelligence used in its problem-solving
agent response that satisfies all the critical tem- method, in-agents can be classified as critical
poral restrictions of the system, its capacities for or acritical. A critical in-agent is characterised
problem-solving, for adaptability and for proactiv- by a period and a deadline. The available time
ity help to provide the best answer for the cur- for the in-agent to obtain a valid response is
rent environment status. Its critical timing require- bounded. It must guarantee a basic response to
ments are 100% guaranteed by means of an off-line the current environment situation. It is formed
schedulability analysis as detailed in [8]. by two layers (see Figure 1): the reflex layer
Basically, the agent must perceive an environ- and the real-time deliberative layer. The first
ment through a set of sensors. After this, the sys- one assures a minimal quality response and the
tem must compute and transmit a response to other second one tries to improve this response. The
agents or the environment using a set of effectors. reflex layer of all the in-agents make up the
The response can be obtained after a reflex process AA mandatory phase. On the other hand,
or a deliberative process. Furthermore, the agent the real-time deliberative layers form the op-
must work with hard temporal restrictions in dy- tional phase. An acritical in-agent only has
namic environments. the real-time deliberative layer. Almost all the
Though the basic AA is designed to work prop- in-agents for real-time environments are criti-
erly under hard real-time restrictions, some of cal in-agents.
the optional features (such as communication with
other agents) may prevent this real-time behaviour • A set of beliefs comprising a world model (with
due to the unpredictable actions they involve. all the domain knowledge which is relevant to
Therefore, it is the agent designer’s decision to the agent) and the internal state. This set is
choose which features (and, therefore, which be- stored in a frame-based blackboard. Temporal
haviours) the agent is going to have. extensions have been incorporated allowing the
The AA architecture could be labeled as a reasoning entities to manage time naturally.
vertical-layered, hybrid architecture with added ex-
tensions to work in a hard real-time environment • The Control Module that is responsible for the
[11]. It is formed by the following elements (see real-time execution of the in-agents that belong
Figure 1): to the AA. The temporal requirements of the
two in-agent layers (reflex and deliberative) are
• A set of sensors and effectors to be able to in- different. Thus, the control module must em-
teract with the environment. Perception and ploy different execution criteria for each one.
action processes are time-bounded. The com- The control module of an AA is divided intotwo submodules: the reflex server and the de- • L = a communication language to be employed
liberative server. by the agents for the interaction processes.
– Reflex server (RS) This module is in • I = {(AAi , AAj )/AAi , AAj ∈ A}, a set of in-
charge of controlling the execution of re- teractions represented by AA pairs. These in-
active components, that is, the compo- teractions show the relations in the system or-
nents with critical temporal restrictions. ganisation.
Due to these restrictions, it is integrated
within a Real-Time Operating System As can be seen, the main component of a Simba
(RTOS). system is the Artis agent, which can be formally
defined as follows:
– Deliberative server (DS) This module is
in charge of controlling the execution of Definition 2 An Artis agent is an structure:
deliberative components. Therefore, this
server is the intelligent element of the con- AAi = hBehavi , Gi , Bi , βi i
trol module, but with temporal restric-
tions. where:
• Behavi is a set of different behaviours of the
AAi for different situations.
real-time [t ,t ] [t ,t ] [t ,t ]
Perception deliberative Action
• Gi = {g1 1 2 , g2 2 3 , . . . , gn n m }, a set of AA
reflex
goals, representing the motivations and restric-
in-agent tions of the agent. The goals are designed
as desired states and they can be temporal
bounded. These temporal restrictions show the
interval in which the goal must be obtained.
control module The goals can be expressed as RTCTL∗ formu-
reflex server
lae [5].
deliberative server
• Bi is the AAi belief set in the current instant.
ARTIS AGENT All the data in this set are time stamped using
a temporal logic as explained in [4].
Figure 1: Artis Agent Architecture
• βi : Gi × Bi → Behavi , a selection function
that determines the current behaviour of the
AAi according to its goals and its beliefs. This
3.2 Formal Approach function corresponds to the AA Control Mod-
Once the Artis agent architecture is presented, a ule.
formal view of the Simba approach is described.
Each behaviour is defined as follows
This formal view allows us to explain the architec-
ture in a more concrete way.
Definition 3 A behaviour beh ∈ Behavi is a set of
in-agents
Definition 1 A Simba architecture is an struc-
beh = {aij }
ture:
Simba = hA, O, L, Ii A behaviour contains the problem-solving knowl-
where: edge. As stated above, an in-agent gives a solution
for a particular problem of the Artis agent.
• A = {AAi }, a countable set of Artis agents,
which are formalised below. Definition 4 An in-agent is an structure
• O = a domain ontology, which specifies the aij = hρij , f ρsel , σij , f σsel , Bij , Dij , Tij i
common vocabulary in order to represent the
system environment. where:• ρij is a set of reflex actions that can be executed
by the in-agent.
• f ρsel : Bij × (Dij , Tij ) → ρij , a selection func-
tion that determines the appropriate reflex ac-
tion to execute by the in-agent according to its
current state and temporal restrictions.
• σij is a set of cognitive actions that can be ex-
ecuted by the in-agent.
SIMBA Communicator
Agent
• f σsel : Bij × (Dij , Tij ) → σij , a selection func-
tion that determines the appropriate cognitive
action to execute by the in-agent according to
its current state and temporal restrictions.
Figure 2: Simba Platform
• Bij ⊂ Bi , is a set of beliefs representing the
internal state and environment of the in-agent.
These beliefs are part of the belief set (Bi ) of • The Agent Management Specification forces
the AAi that the in-agent belongs to. the implementation of a Directory Facilitator
(DF) that provides yellow-pages service to the
• Dij is a deadline, which indicates the greatest agents involved and an Agent Management
time interval in which the in-agent should have System (AMS) which maintains the addresses
executed an action. for agents registered in the platform (white-
pages service).
• Tij is the period, which determines the activa-
tion frequency of the in-agent. This period is
needed due to the external environment’s own • The Agent Communication Language Specifi-
dynamic of RTS. At each period, the in-agent cation contains the message description set to
execution begins reading the new incoming val- be employed in agent interactions.
ues of the data (perceptions) through the ap-
propriate sensors. These new values update the A graphical view of the Simba architecture is
Bij of the in-agent. shown in Figure 2 in accordance with these con-
siderations. As can be seen, it is formed by several
This organisation among AA, behaviours and in- Artis agents and a mediator agent which integrates
agents provides a hierarchy of abstractions which the DF and the AMS services. This mediator agent
structures the problem-solving knowledge in a mod- is the Simba interface with agents that do not fol-
ular and gradual way. One of the main reasons for low the Artis agent architecture. Moreover, the
doing this is to employ the advantages of modular communication language in Simba will obviously
programming, that is, complexity split and code be FIPA-ACL.
reusability. With respect to each Artis agent design, a sin-
gle AA is implemented through a graphical toolkit
3.3 Architecture Design named InSiDE (Integrated Simulation and Devel-
opment Environment) [14] which facilitates the de-
The Simba architecture design is FIPA-compliant sign and debugging of an AA. InSiDE is a visual
in order to allow for future inter-communication toolkit which was developed to allow for agent-
with outer agents from other platforms. A FIPA oriented implementation and management of Ar-
agent platform is defined as software that imple- tis agents. It incorporates an off-line schedulabil-
ments the set of FIPA specifications. To be con- ity analysis, which assures that all the temporal re-
sidered FIPA-compliant, an agent platform imple- strictions are guaranteed a priori. By means of this
mentation must at least implement the Agent Man- toolkit, a user can build a prototype of an Artis
agement [7] and Agent Communication Language Agent, which is directly executable over the RT-
specifications [6]: Linux operating system [8].4 ARTIS Agent communica- in-agent a
tive aspects in-agent b
DS.
slack time
The communication process has to be time-
bounded in some way in order to be considered
within a real-time restricted system such as the AA. Figure 3: Timing diagram example
On the other hand, the whole execution time of
this process cannot be bounded, due to the multi-
ple factors that may affect it, making it very diffi-
5 Example: Intelligent Build-
cult to assure the sending and reception of answers. ings
Moreover, the foreseen interaction processes may be
complex, and they may need to send several mes- In this paper, we present a prototype of a sys-
sages in the same process. tem, developed according to our approach, which
emphasises the multi-agent architecture presented
The main use of the AA communication is to in previous sections. The system we present con-
ask for a service. According to its possible uses, it trols an intelligent building. An intelligent build-
doesn’t seem appropriate to consider the unfulfill- ing is one that utilises computer technology to
ment of a communication process as catastrophic. autonomously govern the building environment so
So, even though the communication process has soft as to optimise user comfort, energy-consumption,
real-time restrictions, it is not possible to assign safety and monitoring-functions [13]. In this exam-
critical temporal restrictions to manage it. ple, we consider a residential building that has dis-
tributed different sensor and actuator devices which
As has been previously mentioned, the part of can be controlled and monitored. Due to the limits
the Control Module in charge of controlling the ex- of the paper only some aspects of the example are
ecution of the non-critical tasks of the AA is the sketched.
Deliberative Server (DS). The DS controls the exe- Three main functionalities can be extracted from
cution of the Communication Module. This module the given definition of an intelligent building:
is in charge of controlling all the low-level peculiar-
ities of a communication process such as message • Safety & Security: the system must take into
construction (according to the communication lan- account system failures such as gas or water
guage), physical media sending and receiving, pars- leaks and detection of intruders.
ing, syntactic checking, etc.
• Comfort: all the aspects related to the building
Figure 3 shows a possible execution stage of an habitability and resident preferences.
AA by a timing diagram. In this example, the AA
is comprised by two in-agents (a and b). Black • Energy-consumption: related to an effective
boxes represent the processor time intervals as- management of energy resources such as elec-
signed to the in-agent reflex layer execution. Be- tricity, gas, diesel or water.
tween these executions, there exists available time
(white boxes). At the beginning of each one of these This system belongs to the social real-time do-
slacks, the DS is executed and it schedules this time mains explained in section 2. There exist critical
taking into account the execution of the Communi- temporal constraints such as alarm activation or
cation Module and the real-time deliberative layers closing/opening valves. Moreover, there exists a
of the in-agents. The DS only launches the Com- clear distribution in the system activities. The co-
munication Module if there is enough slack time to ordination among the entities in the system will im-
assure the sending of at least one message and the prove the global functionality but is not critical for
reception of at least another message. the fulfillment of the critical constraints.
In this case, the Simba system is formed by three
This way of controlling the communication makes agents (see Figure 4): the safety/security agent, the
it possible to communicate without interfering in comfort agent and the energy agent. Each one is in
the fulfillment of critical AA restrictions. charge of controlling its corresponding subsystem.occupied
A = {AAsafety , AAcomfort , AAenergy } emergency
empty
Safety/
Security
Figure 5: State diagram. Safety agent behaviours
Comfort
Energy
and period—. Their knowledge and their reactions
must be the same ones.
Figure 4: Intelligent building control system
behempty = {aleak , asecur }
Each one of these agents is an Artis agent.
Simba allows for the interaction with external, non- Temporal characteristics of in-agents will take
Artis agents through the services supplied by the into account the differences in the sensors and ac-
mediator agent. For instance, it is possible for an tuators sampling. One usual security measure in
agent to ask the system about one of the residents. classic control systems is to achieve that the pe-
The system can verify whether this person is at riod of the system is T2 , where T is the period of
home or not. Some interactions in the system are: the highest-frequency device. The deadline estima-
tion depends on the dynamic of the environment.
• The safety/security agent informs about a sys- It must be such a deadline that allows to solve the
tem failure to the rest of the agents. problem in a satisfactory way for the user. For in-
• The safety/security agent informs the comfort stance, to raise the fire alarm 2 seconds later from
agent that the building is empty in order to to detect smoke. It always must be lower than the
minimise its functionalities. period.
• The energy agent and the comfort agent nego- aleak = {ρleak , 5, 2} asecur = {ρsecur , 30, 10}
tiate different energy resources consumption. It must be always guarantee that the system can
Due to the limits of this paper, we will focus on achieve its goals. That’s why temporal intervals
the safety/security agent. Depending on the pres- which characterise the goals must be less restric-
ence or absence of residents in the building, the tive than the deadline and period of the in-agent
agent shows two different behaviours. If there is responsible of the goal.
nobody in the building, then this agent is the only
entity responsible for safety and security. The dif- 2G(smoke = TRUE → 2F ≤10 alarm = ON )
ference between them lies in the control that the In this RTCTL∗ expression, we are asking the
agent must exert on the building. When it is un- system for a deadline of 10 seconds from the detec-
occupied, the safety/security agent assumes all the tion of smoke to the alarm raising.
responsibilities.
Additionally, another case can be detected: when
a failure has happened—leak or intrusion—and 6 Conclusions
the agent must change its monitoring behaviour
to another, more critical and reactive, to handle This paper shows the Simba architecture, which
it. Figure 5 shows the different behaviours of the is a real-time multi-agent system architecture.
safety/security agent as an state diagram. This architecture shows how a multi-agent oriented
paradigm can be applied to solve problems in so-
Behavsafety = {behocc , behempty , behemerg } cial real-time domains. To do so, it is needed soft-
ware architecture with the appropriate components
Each behaviour must deal with two along with development artifacts adapted to build
responsibilities—leaks and intruders—. So, it this kind of systems.
seems adequate to assign an in-agent to each one. The work described in this paper is the result
In such a case, the in-agents for each behavior of an investigation effort with respect to the appli-
only vary their temporal parameters—deadline cation of interaction processes in an Artis agent.Several questions remain open with respect to new [10] B. J. Grosz. Collaborative systems. AI Maga-
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