ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information Technology Institute of Applied Computer Systems Department of Systems Theory and Design MULTI-AGENT SYSTEMS

2 Single agent So far you know the concept «agent» Definition: An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators. So far we have analysed what stands for the «?»

3 Simple agents Thermostat –The goal is to maintain the room temperature –It is situated in a physical environment checking software –UNIX biff program –Goal is to monitor incoming messages and give alerts to the user –Inhabits in a software environment Are they intelligent?

4 Characteristics of environments Accessible vs Inaccessible Deterministic vs Non-deterministic Episodic vs Sequential Static vs Dynamic Discrete vs Continuous Single-agent vs Multi-agent

5 Multi-agent environment So far multi-agent environment has been mentioned without detailed explanations

6 Agent interactions More complex than object interactions –Agents are autonomous –Can not use traditional method invocation/calling

7 Example: robot can not invoke method of another robot

8 Characteristics of agents in the context of multi-agent systems Reactivity Proactivity Social capabilities

9 Reactivity If the agent’s environment is guaranteed to be in a known state then the actions can be executed blindly Real environments are not like this. Majority of environments are dynamic Development of corresponding software is complex – the possible error must be considered and analysed if the intended action is still appropriate Reactive system continiously monitors the environment and reacts on changes in it in the time for the reaction to be useful

10 Proactivity Reacting on changes is relativelly simple –For example, percept-action rules Still we need the agents to carry out the actions needed for us Thus we need goal directed behaviour Proactivity is goal generation and acting to achieve them. Actions are done based on the agent’s iniative not only by reacting on the events The agent must be capable to see its opportunities

11 Social capabilities Real world is multi-agent environment. To achieve own goals the agent must take into consideration other agents Many goals can be achieved only by interacting with other agents –It is true in many environments, for example, in the Internet Social capabilities are agent’s capabilities to interact with other agents and possibly humans by means of cooperation, coordination and negotiations And finally it implies the capabilities to communicate

12 Multi-Agent system definitions (1/2) Multi-agent system is multiple agents that act in the same environment Multi-agent system is a system that consists of agents that communicate and interact each other to achieve personal or collective goals Multi-agent systems are systems that consist of multiple computational elements that interact each other. These computational elements are named agents

13 Multi-Agent system definitions(2/2) Multi-agent system is a system that consists of multiple agents that interact each other. In general, agents represent users that have different goals. To successfully interact, they must be capable to cooperate, coordinate their actions and negotiate among themselves in the similar manner as humans do

14 Characteristics of multi-agent systems The multi-agent environment must provide cooperation and communication protocols –Agents must be capable to exchange messages Multi-agent system is open and does not have one centralized developer –New agents can be added –They can be added by different developers –Requirement is defined by the Internet Multi-agent systems contain agents that are autonomous, distributed and can have common or individual goals Multi-agent system consists of agents that communicate each other and cooperate to achieve specific personal or collective goals –The agents can not be viewed as isolated entities –They can be understood only by analysing together with the environment where they act and interact with other agents

15 Two aspects of multi agent-systems Individual agents –Very similar ideas to single agent systems Putting together multiple agents (collections) into the same system

16 Multi-agent system

17 Interactions Agents can influence the environment Different agents have different spheres of influence –They can control or at least influence different parts of the environment –Spheres of influence can overlap –Spheres of influence can add new relationships among agents Example of two agents leaving the room threw narrow door Agents may have other relationships –One agent may be a «boss» for another One of the main topics of the multi-agent systems is types of interactions among agents

18 Types of interactions Acting concurrently –Reasoning about actions of other agents –Agent coordination Real (physical) interactions –Message passing

19 Agent coordination Coordination means understanding dependancies among activities and taking them into consideration Examples –Two robotic agents want simultaneously to leave the auditorium using the same narrow door –Two agents want simultaneously to use the same resource The idea is to use the available information to reason about the actions of other agents

20 Agent interactions Q: how can agents exchange information? A: With messages Multiple messages make up negotiations

Multi-agent communications

Agent communication language FIPA ACL –FIPA – Foundation of Intelligent Physical Agents Message based agent communication language Defines general message format Each message can be considered as an object in OO approach. It has: –Performative, that can be considered to state the class of the message –Parameter (pairs of attributes and values) set May include variables

23 Example (inform :sender agent1 :receiver agent2 :content (price good2 150) :language sl :ontology hpl-auction )

24 Types of interactions

25 Cooperation Cooperation is a team work to achieve common goal The reason of cooperation is one of the facts –Agent can not reach the goal alone –The goal can be reached faster as a result of cooperation –The agent can achieve the goal alone, but it would threaten another goal

26 Negotiations Negotiations is finding agreements on the basis of common interests For example there is one TV at home –Wife wants to watch a movie –Husband wants to watch football –Deal: today watching football, tomorrow movie Usually negotiations include offers and counter offers that tend to possible trade-offs

27 Negotiation protocols Specifies –Involved agents and roles –Messages sent among agents and their ordering –Possible actions for an agent in every situation of the negotiation –The protocol is a package that can be reused in similar negotiation scenarios

28 CONTRACT NETWORK Initiator needs some task to be done It announces this task by sending a CFP message to all possible executors After receiving CFP message the agent evaluates if it is capable to do the task It may refuse or make a proposal The initiator then evaluates all proposals and chooses the executor of the task The initiator awards the task to one executor and rejects all other proposals The executor executes the task and informs the initiator about the result