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Titlebook: Adaptive Agents and Multi-Agent Systems; Adaptation and Multi Eduardo Alonso,Daniel Kudenko,Dimitar Kazakov Conference proceedings 2003 Spr

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發(fā)表于 2025-3-28 15:29:30 | 只看該作者
42#
發(fā)表于 2025-3-28 20:15:33 | 只看該作者
43#
發(fā)表于 2025-3-28 23:15:17 | 只看該作者
Finanzierung und Investitionsrechnung,deoff between cooperation and learning in multiagent systems. We focus on multiagent systems where individual agents are capable of solving problems and learning using CBR (Case-based Reasoning). We present several collaboration strategies for agents that learn and their empirical results in several
44#
發(fā)表于 2025-3-29 06:44:57 | 只看該作者
Kosten- und Erfolgscontrolling,we focus on two novel approaches: one is based on a new action selection strategy for Q-learning [.], and the other is based on model estimation with a shared action-selection protocol. The new techniques are applicable to scenarios where mutual observation of actions is not possible..To date, reinf
45#
發(fā)表于 2025-3-29 09:12:07 | 只看該作者
Notger Carl,Rudolf Fiedler,Manfred Kieselearning process?” This paper describes a technique that enables a heterogeneous group of Learning Agents (LAs) to improve its learning performance by exchanging advice. This technique uses supervised learning (back-propagation), where the desired response is not given by the environment but is based
46#
發(fā)表于 2025-3-29 11:48:03 | 只看該作者
https://doi.org/10.1007/978-3-8348-9510-3 from evolutionary theory to the theory and application of multi-agent systems. A key issue is to understand the factors that affect collaboration and communication evolution. To address this problem, here we choose the environmental risk as a compact descriptor of the environment in a model world o
47#
發(fā)表于 2025-3-29 15:35:49 | 只看該作者
Notger Carl,Rudolf Fiedler,Manfred Kieselversity, heterogeneity and fluctuation, confront multiagent learning with new challenges. This paper presents the interaction learning meta-architecture InFFrA as one possible answer to these challenges, and introduces the opponent classification heuristic A.H. as a concrete multiagent learning meth
48#
發(fā)表于 2025-3-29 22:05:51 | 只看該作者
Finanzierung und Investitionsrechnung,smission of language. Using multi-agent computational models we show that certain hallmarks of language are adaptive in the context of cultural transmission. This observation requires us to reconsider the role of innateness in explaining the characteristic structure of language. The relationship bet
49#
發(fā)表于 2025-3-30 01:26:37 | 只看該作者
50#
發(fā)表于 2025-3-30 07:18:57 | 只看該作者
Notger Carl,Rudolf Fiedler,Manfred Kieselby using group or role notions might be very difficult and even impossible for human analysts. Although an organization can be found or approximated, it becomes complicated to design entities, or agents in our case, that take into account, at the conception and design phases, all possible situations
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