ift6802 - h03 commerce electronique agents presentation adaptée des notes de adina florea...

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Ift6802 - H03 Commerce electronique Agents Presentation adapte des notes de Adina Florea Cours a Worcester Polytechnic Slide 2 Lecture outline n Motivation for agents n Definitions of agents agent characteristics, taxonomy n Agents and objects n Multi-Agent Systems n Agents intelligence n Examples Slide 3 Contexte de techno agents n Besoin de composantes logicielles robustes et flexibles n Opportunisme: prendre avantage de ressources disponibles n Prvoir lexploitation de limprvisible n Autonomie, intelligence, volution 3 Slide 4 Motivations for agents n Large-scale, complex, distributed systems: understand, built, manage n Open and heterogeneous systems - build components independently n Distribution of resources n Distribution of expertise n Needs for personalization and customization n Interoperability with legacy systems 4 Slide 5 Questions: Programs or agents? a thermostat with a sensor for detecting room temperature electronic calendar (arranges meetings) Email system with messages sorted by date Email with messages sorted by order of importance and SPAM deleted Bidding program for electronic auctions 5 Slide 6 Agent? The term agent is used frequently nowadays in: Sociology, Biology, Cognitive Psychology, Social Psychology, and Computer Science AI Why agents? What are they in Computer Science? Do they bring us anything new in modelling and constructing our applications? Much discussion of what (software) agents are and of how they differ from programs in general 6 Slide 7 What is an agent (en informatique)? n There is no universally accepted definition of the term agent and there is a good deal of ongoing debate and controversy on this subject n The situation is somehow comparable with the one encountered when defining artificial intelligence. n Confluence de plusieurs groupes de recherche: Informatique distribue IA Sociologie & Economie Vie artificielle / simulation 7 Slide 8 n More than 30 years ago, computer scientists set themselves to create artefacts with the capacities of an intelligent person (artificial intelligence ). n Now we are facing the challenge to emulate or simulate the way human act in their environment, interact with one another, cooperatively solve problems or act on behalf of others, solve more and more complex problems by distributing tasks or enhance their problem solving performances by competition. 8 Slide 9 n Are agents intelligent? n Not necessarily. n Not to enter a debate about what intelligence is n Agent = more often defined by its characteristics - many of them may be considered as a manifestation of some aspect of intelligent behaviour. 9 Slide 10 Agent definitions n Most often, when people use the term agent they refer to an entity that functions continuously and autonomously in an environment in which other processes take place and other agents exist. (Shoham, 1993) n An agent is an entity that senses its environment and acts upon it (Russell, 1997) Slide 11 11 Agent & Environment Agent Environment Sensor Input Action Output Slide 12 n Autonomous agents are computational systems that inhabit some complex dynamic environment, sense and act autonomously in this environment, and by doing so realise a set of goals or tasks for which they are designed. (Maes 1995) n Intelligent agents continuously perform three functions: perception of dynamic conditions in the environment; action to affect conditions in the environment; and reasoning to interpret perceptions, solve problems, draw inferences, and determine actions. (Hayes-Roth 1995) n Intelligent agents are software entities that carry out some set of operations on behalf of a user or another program, with some degree of independence or autonomy, and in so doing, employ some knowledge or representation of the users goals or desires. (the IBM Agent) 12 Slide 13 Niveaux dagents Loop percevoir environnement et attendre qqc a faire decider quoi faire prendre action n Controlleur ractifs Daemon logiciels Thermostat, spool in/out, serveurs Slide 14 Identified characteristics Two main streams of definitions n Define an agent in isolation n Define an agent in the context of a society of agents social dimension MAS Two types of definitions n Does not necessary incorporate intelligence n Must incorporate a kind of IA behaviour intelligent agents 14 Slide 15 n Interesting Agent = a hardware or software-based computer system that enjoys the following properties: autonomy - agents operate without the direct intervention of humans or others, and control their actions and state; reactivity: agents perceive their environment and respond in a timely fashion to changes that occur in it; complexity: manipulating the environment is not trivial pro-activeness: agents do not simply act in response to their environment, they are able to exhibit goal-directed behaviour by taking initiative. social ability - agents interact with other agents (and possibly humans) via some kind of agent- language; (Wooldridge and Jennings, 1995) 15 Slide 16 Agents characteristics n function continuously / persistent software n sense the environment and acts upon it / reactivity n act on behalf of a user or a / another program n autonomous n purposeful action / pro-activity goal-directed behavior vs reactive behaviour? n mobility ?intelligence? n Goals, rationality cognitive n Reasoning, decision makingcognitive n Learning/adaptation n Interaction with other agents - social dimension Other basis for intelligence? 16 Slide 17 17 Agent Environment Agent Environment Sensor Input Action Output Environment properties - Accessible vs inaccessible - Deterministic vs nondeterministic - Episodic vs non-episodic - Static vs dynamic - Open vs closed - Contains or not other agents Slide 18 n Interactions among agents - high-level interactions n Interactions for- coordination - communication - organization o Coordination collectively motivated / interested self interested - own goals / indifferent - own goals / competition / competing for the same resources - own goals / competition / contradictory goals - own goals / coalitions 18 MAS - many agents in the same environment Slide 19 o Communication communication protocol communication language - negotiation to reach agreement - ontology o Organizational structures centralized vs decentralized hierarchical/ markets "cognitive agent" approach MAS systems? n Electronic calendars n Air-traffic control system 19 Slide 20 20 The wise men problem A king wishing to know which of his three wise men is the wisest, paints a white spot on each of their foreheads, tells them at least one spot is white, and asks each to determine the color of his spot. After a while the smartest announces that his spot is white Slide 21 Agents vs Objects n Les agents sont le rsultat dune progression continue dans lvolution des concepts dabstraction en informatique. 21 Slide 22 Agents vs Objects n Autonomy - stronger - agents have sole control over their actions, an agent may refuse or ask for compensation n Flexibility - Agents are reactive, like objects, but also pro- active n Agents are usually persistent n Own thread of control Agents vs MAS n Coordination - as defined by designer, no contradictory goals n Communication - higher level communication than object messages n Organization - no explicit organizational structures for objects n No prescribed rational/intelligent behaviour 22 Slide 23 Ferber: n An agent is a physical or virtual entity 1. which is capable of acting in an environment. 2. which can communicate directly with other agents. 3. which is driven by a set of tendencies (in the form of individual objectives or of a satisfaction/survival function which it tries to optimize). 4. which possesses resources of its own. 5. which is capable of perceiving its environment (but to a limited extent). 6. which has only a partial representation of its environment (and perhaps none at all). 7. which possesses skills and can offer services. 8. which may be able to reproduce itself. 9. whose behaviour tends towards satisfying its objectives, taking account of the resources and skills available to it and depending on its perception, its representation and the communications it receives. 23 Slide 24 Ferber: n Multi Agent System 1. An environment E, that is, a space which generally has volume. 2. A set of objects, O. These objects are situated, that is to say, it is possible at a given moment to associate any object with a position in E. 3. An assembly of agents, A, which are specific objects (a subset of O), represent the active entities in the system. 4. An assembly of relations, R, which link objects (and therefore, agents) to one another. 5. An assembly of operations, Op, making it possible for the agents of A to perceive, produce, transform, and manipulate objects in O. 6. Operators with the task of representing the application of these operations and the reaction of the world to this attempt at modification, which we shall call the laws of the universe. 24 Slide 25 There are two important special cases of this general definition. n Purely situated agents n An example would be a robot. In this case E, the environment, is Euclidean 3- space. A are the robots, and O, not only other robots but physical objects such as obstacles. These are situated agents. n Pure Communication Agents n If A = O and E is empty, then the agents are all interlinked in a communication networks and communicate by sending messages. We have a purely communicating MAS. 25 Slide 26 How do agents acquire intelligence? Cognitive agents The model of human intelligence and human perspective of the world characterise an intelligent agent using symbolic representations and mentalistic notions: knowledge - John knows humans are mortal beliefs - John took his umbrella because he believed it was going to rain desires, goals - John wants to possess a PhD intentions - John intends to work hard in order to have a PhD choices -