Add to ORKGDistribution unlimited 13,ABSTRACT Maximum 00 worasJ One of the interesting characteristics of multi-agent problem solving in distributed artificial intelligence (DAI) systems / is that the agents are able to learn from each other, thereby facilitating the problem-solving process and enhancing the/ quality of the solution generated. This paper aims at studying the multi-agent learning mechanism involved in a specific group learning situation: the induction of concepts from training examples. Based on the mechanism, a distribute
The intelligent control of multiple autonomous agents is an important yet difficult task. Previous m...
Abstract: "In this paper we propose a distributed approach to the inductive learning problem and pre...
This thesis has introduced and investigated a new kind of rule-based evolutionary online learning sy...
Abstract: "One of the interesting characteristics of multi-agent problem solving in distributed arti...
A distributed problem-solving approach to rule induction: learning in distributed artificial intelli...
Groups of agents following fixed behavioral rules can be limited in performance and efficiency. Adap...
Proceeding of: 6th Ibero-American Conference on AI (IBERAMIA '98),Lisbon, Portugal, October 5–9, 199...
this paper only presents preliminary, propositional results which do not reflect the more complex as...
This paper presents a study on a rule induction application for generating an agent strategy. It is ...
Groups of agents following fixed behavioral rules can be limited in performance and etficiency. Adap...
Artificial intelligence algorithms enable autonomous agents to perform sophisticated tasks with grea...
This paper is devoted to the problem of reinforcement learning in multi-agent systems. Multi-agent s...
Abstract. Argumentation can be used by a group of agents to discuss about the validity of hypotheses...
In this paper, we tackle learning in distributed systems and the fact that learning does not necessa...
Abstract — In this paper, we tackle learning in distributed systems and the fact that learning does ...
The intelligent control of multiple autonomous agents is an important yet difficult task. Previous m...
Abstract: "In this paper we propose a distributed approach to the inductive learning problem and pre...
This thesis has introduced and investigated a new kind of rule-based evolutionary online learning sy...
Abstract: "One of the interesting characteristics of multi-agent problem solving in distributed arti...
A distributed problem-solving approach to rule induction: learning in distributed artificial intelli...
Groups of agents following fixed behavioral rules can be limited in performance and efficiency. Adap...
Proceeding of: 6th Ibero-American Conference on AI (IBERAMIA '98),Lisbon, Portugal, October 5–9, 199...
this paper only presents preliminary, propositional results which do not reflect the more complex as...
This paper presents a study on a rule induction application for generating an agent strategy. It is ...
Groups of agents following fixed behavioral rules can be limited in performance and etficiency. Adap...
Artificial intelligence algorithms enable autonomous agents to perform sophisticated tasks with grea...
This paper is devoted to the problem of reinforcement learning in multi-agent systems. Multi-agent s...
Abstract. Argumentation can be used by a group of agents to discuss about the validity of hypotheses...
In this paper, we tackle learning in distributed systems and the fact that learning does not necessa...
Abstract — In this paper, we tackle learning in distributed systems and the fact that learning does ...
The intelligent control of multiple autonomous agents is an important yet difficult task. Previous m...
Abstract: "In this paper we propose a distributed approach to the inductive learning problem and pre...
This thesis has introduced and investigated a new kind of rule-based evolutionary online learning sy...