MULTI AGENT SYSTEMS

MULTI-AGENT SYSTEMS Reference  [1] Michael Wooldridge, “An Introduction to MultiAgent Systems”, Second Edition, 2009  [2] R.H. Bordini, J.F.Hubner, M. Wooldridge, “Programming multi- agent systems in AgentSpeak using Jason”, 2007. 2 Outline  Background  Agent  Environment  Architecture for Agents Reading: Chapter 1&2, [1] 3 Background  Distributed Artificial Intelligence (DAI)  Subfield of AI  Development of distributed solutions for complex problems  problem that is beyond the capability of an individual problem solver  Two mainstreams  Distributed prolem solving (DPS)  MultiAgent systems (MAS) 4 Background  Distributed Artificial Intelligence (DAI)  Two mainstreams  Distributed prolem solving (DPS)  Centralized Control, Distributed Data  MultiAgent systems (MAS)  Distributed Control, Distributed Data  a system comprising several agents that “live” and interact in the same environment. 5 Outline  Background  Agent  Environment  Architecture for Agents 6 Example  Cleaning robot  Gold miners 7 What is an Agent?  There is no universally accepted definition of the term “Agent”  There is a general consensus that autonomy is central to the notion of agency.  Difficulty is that various attributes associated with agency are of diffening importance for different domains. 8 What is an Agent?  Autonomy:  capable of acting independently,  exhibiting control over their internal state  Thus: an agent is a computer system capable of autonomous action in some environment in order to meet its design objectives 9 SYSTEM ENVIRONMENT input output What is an Agent?  An agent in its environment 10 Environment ? Sensors Feedback Actions [...]... cooperation of others  Social ability in agents is the ability to interact with other agents (and possibly humans) via some kind of agent- communication language, and perhaps cooperate with others 17 Outline  Background  Agent  Environment  Abstract Architecture for Agents 23 Environments Accessible vs inaccessible  An accessible environment is one in which the agent can obtain complete, accurate,... over time 31 Outline  Background  Agent  Environment  Abstract Architecture for Agents 32 Architecture for Agents  Logic-Based Architectures  Reactive Architectures  BDI Architectures  Layered Architectures (Hybrid) 33 BDI Architectures  BDI = Belief – Desire - Intention  Beliefs:  information the agent has about world  Desires:  states of affairs that the agent, in an ideal world, would wish... can be assumed to remain unchanged except by the performance of actions by the agent  A dynamic environment is one that has other processes operating on it, and which hence changes in ways beyond the agent s control 28 Environments Static vs dynamic  Other processes can interfere with the agent s actions (as in concurrent systems theory)  The physical world is a highly dynamic environment  Example:...What is an Agent?  In most domain of reasonable complexity, an agent will not have complete control over its environment   It will have at best partial control, in that it can influence it 11 What is an Agent?  Trivial (non-interesting) agents:  Thermostat  Have a sensor for detecting room temperature  Two signals: too... it (in time for the response to be useful) 15 Proactiveness  we generally want agents to do things for us  goal directed behavior  Pro-activeness = generating and attempting to achieve goals; not driven solely by events; taking the initiative  Recognizing opportunities 16 Social Ability  The real world is a multi- agent environment: we cannot go around attempting to achieve goals without taking... and heating off  Rules:  Too cold  heating on  Temperature Ok  heating off  When the door of the room is close?  guaranteed effects  When the door of the room is open? 12 What is an Agent?  An intelligent agent is a computer system capable of flexible autonomous action in some environment  By flexible, we mean:  reactive  pro-active  social 13 Reactivity  If a program’s environment is guaranteed... example, the everyday physical world and the Internet) are inaccessible 24 Environments Accessible vs inaccessible  The more accessible an environment is, the simpler it is to build agents to operate in it  Example:  a vacuum agent with only a local dirt sensor cannot tell whether there is dirt in other squares,  an automated taxi cannot see what other drivers are thinking 25 Environments Deterministic... Intentions  desires that the agent has committed to achieving Belief-Desire-Intention Environment belief sense act revision Beliefs generate options filter Desires Intentions BDI model implementation  Beliefs > prolog like facts  Desires and intentions are realized from plan library  Plans achieve some state of affairs  A plan has body and invocation condition  The agent picks one desires and... library  Plans achieve some state of affairs  A plan has body and invocation condition  The agent picks one desires and puts it on execution stack  Execution stack are intentions Example  Cleaning agent . MULTI- AGENT SYSTEMS Reference  [1] Michael Wooldridge, “An Introduction to MultiAgent Systems , Second Edition, 2009  [2]. Wooldridge, “Programming multi- agent systems in AgentSpeak using Jason”, 2007. 2 Outline  Background  Agent  Environment  Architecture for Agents Reading: