Adaptive agents and multi-agent systems : adaptation and multi-agent learning
Adaptive Agents and Multi-Agent Systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, computer science, software engineering, and developmental biology, as well as cognitive and social science. This book surveys the state of the art...
Enregistré dans:
| Autres auteurs: | , , |
|---|---|
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Collection: | Lecture notes in computer science. Lecture notes in artificial intelligence
2636 |
| Sujets: | |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Communications choisies, présentées aux 1er et 2ème symposia Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Adaptive agents and multi-agent systems, adaptation and multi-agent learning, Eduardo Alonso, Daniel Kudenko, Dimitar Kazakov (eds.), Berlin, Springer, 2003, 1 vol. (XIV-322 p.), Lecture notes in computer science, 3-540-40068-0 • Adaptive Agents and Multi-Agent Systems, Texte imprimé, 9783662178201 |
Table des matières:
- Learning, Co-operation, and Communication
- Cooperative Multiagent Learning
- Reinforcement Learning Approaches to Coordination in Cooperative Multi-agent Systems
- Cooperative Learning Using Advice Exchange
- Environmental Risk, Cooperation, and Communication Complexity
- Multiagent Learning for Open Systems: A Study in Opponent Classification
- Situated Cognition and the Role of Multi-agent Models in Explaining Language Structure
- Emergence and Evolution in Multi-agent Systems
- Adapting Populations of Agents
- The Evolution of Communication Systems by Adaptive Agents
- An Agent Architecture to Design Self-Organizing Collectives: Principles and Application
- Evolving Preferences among Emergent Groups of Agents
- Structuring Agents for Adaptation
- Stochastic Simulation of Inherited Kinship-Driven Altruism
- Theoretical Foundations of Adaptive Agents
- Learning in Multiagent Systems: An Introduction from a Game-Theoretic Perspective
- The Implications of Philosophical Foundations for Knowledge Representation and Learning in Agents
- Using Cognition and Learning to Improve Agents Reactions
- TTree: Tree-Based State Generalization with Temporally Abstract Actions
- Using Landscape Theory to Measure Learning Difficulty for Adaptive Agents
- Relational Reinforcement Learning for Agents in Worlds with Objects.