anchor 发表于 2025-3-27 00:12:00

Der Leistungserstellungsprozess,stricted two-agent model, in which agents are represented by finite automata, and one of the agents plays a fixed strategy. We show that even with this restrictions, the learning process may be exponential in time..We then suggest a criterion of simplicity, that induces a class of automata that are learnable in polynomial time.

chemical-peel 发表于 2025-3-27 03:27:05

BRST Symmetry in Constrained Systems, is intended to provide a compact, introductory and motivational guide to this topic. The article consists of two sections. In the first section,“Remarks”, the range and complexity of this topic is outlined by taking a general look at the concept of multi-agent systems and at the notion of adaptatio

共栖 发表于 2025-3-27 08:53:02

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熟练 发表于 2025-3-27 10:54:14

BRST Symmetry and de Rham Cohomology interactive strategy is a hard problem because it depends mostly on the behavior of the others. In this work, interaction among agents is represented as a repeated two-player game, where the agents‘ objective is to look for a strategy that maximizes their expected sum of rewards in the game. We ass

主讲人 发表于 2025-3-27 13:39:34

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limber 发表于 2025-3-27 19:05:13

https://doi.org/10.1007/978-3-642-71795-6e and strategic behavior. Agents that operate in dynamic environments could react to unexpected events by generalizing what they have learned during a training stage‘..In this paper, we propose several learning rules for agents in a multiagent environment. Each agent acts as the teacher of its partn

不能妥协 发表于 2025-3-28 00:41:56

The Buyographics of Health Care,e interrelated tasks in a real-time environment. DRLM consists of a hidden task model (HTM) used for dealing with incomplete perception, a composite state model (CSM) for interdependency between tasks, and a .-learning subsystem (QLS) for updating action merit. In this paper, we also present a distr

表被动 发表于 2025-3-28 04:30:26

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Arable 发表于 2025-3-28 06:33:27

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大猩猩 发表于 2025-3-28 13:09:04

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查看完整版本: Titlebook: Adaptation and Learning in Multi-Agent Systems; IJCAI‘ 95 Workshop, Gerhard Weiß,Sandip Sen Conference proceedings 1996 Springer-Verlag Be