Systèmes Multi-Agents

1. Systèmes Multi-Agents Conception Applications J. Ferber, "Les systèmes multi agents", InterEditions, 1995 http://www-poleia.lip6.fr/~drogoul/cours/links.html Certificat IMTC et Master ISM

2. Part I - Conception • 1. Motivations et origines • 2. Problèmes et definitions • 3. Le principe d’interaction • 4. L’architecture blackboard Certificat IMTC et Master ISM

3. 1. - Motivations et origines • Systèmes actuels: unicité de l'expert trop souvent considérée • se rapprocher de la réalité décisionnelle: • faire apparaître la multiplicité des experts et la multiplicité des relations entre experts (coopération, compétition, négotiation,…) • du décideur individuel aux réseaux de décideurs: • population d'agents autonomes en interaction • métaphore des organisations • on met l'accent sur l'interaction Certificat IMTC et Master ISM

4. 1. - Motivations et origines • Première définition • SMA: un système dans lesquels des agents artificiels opèrent collectivement et de façon décentralisée pour accomplir une tâche. • Ces entités peuvent être implantées sur un support physique ou logique (entités matérielles ou immatérielles) ; Certificat IMTC et Master ISM

5. 1. - Motivations and origins • 1.1. Evolution of the theory of mind • 1.2. Limitation of classical AI • 1.3. Evolution of the computer programming paradigm Certificat IMTC et Master ISM

6. 1.1. - Evolution of the theory of mind • Development in the 70th of the theory of mind which postulate that : • Intelligence is relying on individual competences + ability to interact with a physical and social environment (eg perceive and communicate) ; • Reasoning does not resume to applying an a priori fixed sequence of expert rules but rather imply a collection of concurrent, heterogeneous and dynamically evolving processes ; • Two simultaneous and complementary trends : Minsky - The Society of Mind / Vygotsky - The Mind in Society ; Certificat IMTC et Master ISM

7. Minsky - The Society of Mind • A useful metaphor to think of intelligence is to consider a large system of experts or agencies that can be assembled together in various configurations to get things done ; • Minsky said, « ...each brain contains hundreds of different types of machines, interconnected in specific ways which predestine that brain to become a large, diverse society of partially specialized agencies » ; • Cognition is a distributed phenomenon ; • [Minsky 85] Certificat IMTC et Master ISM

8. Vygotsky - The Mind in Society • The mind in society : the origins of individual psychological functions are social ; • Every high-level cognitive function appears twice: first as an inter-psychological process and only later as an intra-psychological process ; • The new functional system inside the child is brought into existence in the interaction of the child with others (typically adults) and with artifacts ; • As a consequence of the experience of interactions with others, the child eventually may become able to create the functional system in the absence of the others ; • [Vygotsky 78] Certificat IMTC et Master ISM

9. The distributed cognition paradigm • Cognition is no more envisaged as a purely local and isolated information processing but rather considered as : • Context-dependent ; • Temporally distributed : past reasoning may influence current processings ; • Involving cooperation and communication with the physical and social environment ; • Dynamically evolving as the result of its processings and interactions ; • [Hutchin 95] Certificat IMTC et Master ISM

10. 1.2. - Limitation of classical AI • Considering problems of increasing complexity : • Problems that are physically and functionally distributed ; • Problems that involve heterogeneous data and expertise ; • Problems in which data, information and knowledge is uncertain, incomplete and dynamically evolving ; • Problems that can not be tackled by global problem solving methods ; Certificat IMTC et Master ISM

11. Physical distribution From [Miksch 96] Certificat IMTC et Master ISM

12. Physical distribution Certificat IMTC et Master ISM

13. Functional distribution • Task example : patient monitoring • Sensing, interpretation and summarization of patient data ; • Detection, diagnosis, and correction of critical situations ; • Construction, refinement and revision of short-term and long-term therapy plans ; • Control and supervision of monitoring devices ; • Explanation of observations, diagnoses, predictions, and therapies based on the underlying anatomy and physiology ; Certificat IMTC et Master ISM

14. Acquisition of clinical data Choice of hypothesis Evocation of diagnosis hypothesis Interpretation of test result Choice of procedure Facilitating or Restricting Conditions Choice of tests Certificat IMTC et Master ISM

15. Heteregoneus knowledge and expertise • Various type of knowledge • Clinical Knowledge of common problems, symptoms and treatments ; • Biological knowledge of anatomy, physiology and pathophysiology ; • Knowledge of fundamental physical models and fault conditions ; • Various types of expertise • Patient monitoring : a team work involving members with complementary tasks and skills, • which is most often staffed with new or inexperienced physicians and nurses ; Certificat IMTC et Master ISM

16. Complexity requires a local view • Complex system behaviour often emerge as the dynamic interaction between : • The system components ; • The system as a whole with the environment ; • The environment with the individual components ; • The resulting dynamics, at the system level, may influence the environment which in turn will influence the component dynamics ; • Even when a clean formulation is possible, analytical approaches often involves concurrent expansion of recursive functions ; Certificat IMTC et Master ISM

17. Complexity as dynamicity of interactions… System Environment Comp.2 Comp.1 Comp.N Certificat IMTC et Master ISM

18. Decentralization as an alternative view • An alternative to the classical approach based on a single monolithic system is the divide and conquer principle where a phenomenon is viewed as composed of a set of related and interacting sub-phenomena ; • The whole phenomenon is then described by several (hererogeneous) models accounting for its component behaviours, together with several (heterogeneous) models accounting for their interactions ; • Instead of designing a single « heavy » all-purpose system, this approach creates « light », case-based, narrow-minded units that have clearly identified objectives and background information necessary to successfully achieve their objectives ; Certificat IMTC et Master ISM

19. Decentralization as an alternative view • While in the first case the model of the whole phenomenon to be regulated is contained in a single unit, in the second case a number of partial models of the phenomenon are contained in several units ; • Each of these units can regulate just a single part of the entire phenomenon ; • A global view for the whole phenomenon simply emerges from the structured interaction of the partial units ; Certificat IMTC et Master ISM

20. Complexity to deal with complexity… • Main advantages : • A complex global model usually depends on several parameters that are difficult to identify and to measure ; • Models with higher degree of approximation with respect to the real phenomenon may be derived, because the decomposition allows to develop sub-models for very specific contexts ; • Alternative sub-models may be employed for describing the same phenomenon (competitive models) ; • Since the sub-parts of the phenomenon may overlap, the actions that each unit undertake to regulate these sub-parts may conflict ; fusion and/or negotiation mechanisms are then required ; Certificat IMTC et Master ISM

21. 1.3. - Evolution of the computer programming paradigm • Toward more effective design and re-use : • Looking for high specification levels ; • Looking for fault tolerant design ; • Looking for more expressive representation, more accurate operative perspective ; • Toward increased man-machine communication capabilities… Certificat IMTC et Master ISM

22. Certificat IMTC et Master ISM

23. Towards autonomous systems • Complexity increases in such a way that the expression or prevision of all possible cases becomes prohibitive. • There is a shift, from a compositionality hypothesis to an autonomy hypothesis of the system components ; • This suggests to design entities fitted with own laws, to augment their capacity of internal adaptation, and thus of autonomy and autoorganisation ; • [Courant 94] Certificat IMTC et Master ISM

24. 2. - Issues and definitions • An agent is a computer system situated in some environment, that is capable of autonomous action in this environment in order to meet its design objectives ; • Autonomy : the agent should be able to act without the direct intervention of humans (or other agents), and should have control over its own actions and internal state ; • Multi-agent system : a set of agents interacting in the exploitation of a common environment, toward a common global goal ; Certificat IMTC et Master ISM

25. By definition • Multi-Agent Systems are such that: • Each agent has incomplete information or capabilities to solve a problem ; • There is no global system control, nor any global view of the system given to any single agent (except the human one…) ; • Computation is asynchronous ; • In addition, mobile agents may be designed, that have the ability to traverse a computer network accumulating information from several sites (eg online monitors, nurses reporting stations, patient records, doctors at remote locations…) ; Certificat IMTC et Master ISM

26. Designing styles • Deux aspects à traiter: • Aspects microscopiques (orientés agent) • comment construire un agent capable d'agir de manière autonome, • quelles sont ses représentations et ses comportements • Aspects macroscopiques (orientés système) • comment construire une organisation capable d'agir de manière coopérative • quels sont ses moyens de communication et de coordination Certificat IMTC et Master ISM

27. Designing styles • A multi-agent system may be : • Open : the set of agents is not predefined, new agents may be created on demand ; • Closed : the set of agents is fixed in advance ; • Homogeneous : all agents obey the same model ; • Heterogeneous : agents fitted with different models, operating at various levels of grain, may co-exit ; • Hybrid : human and non-human agents may collaborate « anonymously » to perform the task at hand ; Certificat IMTC et Master ISM

28. Agent models Knowledge base Control unit cooperative planning layer social models local planning layer mental models Knowledge Abstraction behaviour- based layer world models Perception Action Environnement Certificat IMTC et Master ISM

29. Agent Models : Cognitive 1. Contrôle (buts, plans, tâches) 2. Expertise du domaine 3. Connaissances sur soi-même et sur les autres (croyances) 4. Communications Certificat IMTC et Master ISM

30. Agent Models : Réactive 1. Contrôle 2. Comportements 3. Perception 4. Reproduction Certificat IMTC et Master ISM

31. Agent behaviour • Do forever • Receive observation (percept) ; • Update internal model (beliefs) ; • Deliberate to form intentions ; • Use intentions to plan actions (means-end reasoning) ; • Execute plan ; • Two essential points : • The agents have bounded resources (including time) ; • The world changes while deliberating, planning and executing and this can result in intentions and plans being invalidated ; Certificat IMTC et Master ISM

32. Agents as intentional systems • Predominant approach: treat agents as intentional systems that may be understood by attributing to them mental states such as : • The beliefs that agents have ; • The goals that agents will try to achieve ; • The actions that agents perform ; • The ongoing interaction ; Certificat IMTC et Master ISM

33. 3. - The interaction principle • Interaction = • Communication + • Task allocation + • Cooperation + • Coordination of actions + • Resolution of conflict Certificat IMTC et Master ISM

34. Modes de Communication • Communications directes (ou explicites) : l'échange direct est réalisé volontairement en direction d'un individu ou groupe d'individus • communication par partage d'informations: • les agents lisent et déposent une information sur une zone de données commune (eg tableau noir) • communication par envoi de messages (notion de protocole) • communication point à point (téléphone) • communication par diffusion (broadcast) • Communications indirectes (ou implicites) : • les agents laissent des traces (signaux) de leur présence ou de leur action qui sont perçues par d'autres agents • l’environnement propage (et éventuellement déforme) les signaux déclenchés par la réalisation d’une action; cela entraîne des types d'échanges limités et permet de ne pas avoir à déterminer précisément le rôle de chaque individu dans le traitement collectif (ex les objets dans l'environnement émettent des signaux ou des champs de potentiels guidant les agents) Certificat IMTC et Master ISM

35. Agent KS Agent KS Agent Agent KS Blackboard Commmunication types Message passing Message Information sharing Infor- mation Certificat IMTC et Master ISM

36. Messages et Acteurs • Le modèle acteur: centré sur le principe du message • les acteurs sont réactifs, ils mettent en oeuvre un traitement en réponse à un message reçu d'un autre acteur, et sont capables d'envoyer des messages à d'autres acteurs. • Comportement: • exécuter une action • envoyer un message à lui-même ou à d'autres acteurs • créer d'autres acteurs • spécifier un comportement de remplacement • Fonctionnement: • à réception d'un message, vérifie si le message matche le comportement de l'acteur • si OK, exécute l'action correspondante; • principe de continuation: désigne l'acteur auquel envoyer le résultat du message • peut éventuellement déléguer à un autre (proxy) Certificat IMTC et Master ISM

37. Agent situé ou communiquant • Agent purement situé: • l'environnement possède une métrique, • les agents sont situés à une position dans l'environnement qui détermine ce qu'ils perçoivent; • ils peuvent se déplacer; • il n'y a pas communications directes entre agents, elle se font via l'environnement • Agent purement communiquant: • il n'y a pas d'environnement au sens physique du terme, • les agents n'ont pas d'ancrage physique, • ils communiquent via des informations qui circulent entre les agents Certificat IMTC et Master ISM

38. Situé ou Communiquant • Société de Fourmis • La résolution du problème s'inscrit dans l'environnement physique et dans l'organisation physique trouvée par les agents • Réseau de décideurs • la résolution du problème s'inscrit dans une structure conceptuelle et dans les modes de coopération enre agents Certificat IMTC et Master ISM

39. Agents Réactifs Situés (exemple) • Problème: un ensemble de robots doivent trouver du minerai et le rapporter à la base Certificat IMTC et Master ISM

40. Agents Réactifs Situés (exemple) • Règle Explorer si je ne porte rien et je ne perçois aucun minerai et je ne perçois aucune marque alors j'explore de manière aléatoire • Règle SuivreMarque si je ne porte rien et je ne perçois aucun minerai et je perçois une marque alors je me dirige vers cette marque • Règle Trouver si je ne porte rien et je perçois du minerai alors je prends un échantillon de minerai • Règle Rapporter si je porte du minerai et je ne suis pas à la base alors retourner à la base et déposer une marque • Règle Déposer si je porte du minerai et je suis à la base alors déposer le minerai Certificat IMTC et Master ISM

41. Task allocation • Objectives • Decompose the problem into sub-problems ; • Allocate the tasks to agents, according to their competences and specialities ; • Re-organize during execution if necessary ; • Approach • Static : the allocation is performed a priori by the system designer ; • Dynamic : the allocation is performed by the agents themselves (eg contract net) ; • Hybrid : the initial allocation my be revised to account for changes in the environment (case of an open architecture in particular) ; Certificat IMTC et Master ISM

42. The Contract Net • Objective : given a task to perform, allocate it to the « best » agent, knowing the task characteristics, its eventual realization constraints, and considering the agent potential and effective capabilities to succeed ; • 3 main steps : • Sending of a call for a task / reception of the proposals by the contacted agents ; • Selection of the best proposals / establishment of the contract(s) / reception of the result(s) ; • Selection / construction of final result ; Certificat IMTC et Master ISM

43. Who can? JKL Sending a call for a task I can 0.95 I can 0.85 I can 0.45 Receiving the proposals You realize JK Selecting (some) proposer(s) I realize 0.75 I realize 0.55 Receiving the answers J Give me Constructing the final result There it is The Contract Net Certificat IMTC et Master ISM

44. Cooperation styles • Three cooperation styles may be distinguished [Hoc 96] : • Confrontative cooperation : a task is performed by agents with heteregoneous competencies or viewpoints, operating on the same data set ; the result is obtained by fusion ; the emphasis is on competence distribution ; • Augmentative cooperation : a task is performed by agents with similar competencies or viewpoints, operating on disjoint subsets of data ; the result is obtained as a collection of partial results ; the emphasis is on data distribution : • Integrative cooperation : a task is decomposed into sub-tasks performed by agents operating in a coordinated way ; the result is obtained upon execution completion ; the emphasis is on goal distribution ; Certificat IMTC et Master ISM

45. Agent 3 Agent 2 Agent 1 Confrontative cooperation Certificat IMTC et Master ISM

46. Agent 5 Agent 6 Agent 3 Agent 2 Agent 4 Augmentative cooperation Agent 1 Certificat IMTC et Master ISM

47. Agent 2 Agent 1 Agent 3 Agent 4 Integrative cooperation Certificat IMTC et Master ISM

48. Coordination of actions • How to plan and coordinate the actions of several agents in order to reach a common goal? • Two main modes : • Planning (centralized or distributed) ; • Opportunistic problem solving ; Certificat IMTC et Master ISM

49. Planning • Centralized planning • A centralized manager distributes the plans to every agent, having the knowledge of their competences + competencies in task decomposition ; • Easiest way to maintain consistency of problem solving but not too far from classical planning ; • Distributed planning • Each agent produces partial plans and communicate them to the other agents or to a mediator ; • Issues : fuse/synchronize the plans in a consistent way ; avoid duplication of efforts + conflicts ; dynamic planning? • Heavy communication load, high complexity ; Certificat IMTC et Master ISM

50. Opportunistic problem solving • The system « simply » chooses a next action at each step, as the one that will allow the best progress toward the solution, given the curent situation (ie the available data and the intermediate state of problem solvng) ; • Strongly data-directed, allow rapid refocusing (at each control cycle) ; • Implies some knowledge of action cost and utility ; Certificat IMTC et Master ISM