EPMAS: Evolutionary Programming Multi-Agent Systems
نویسندگان
چکیده
Evolutionary Programming (EP) seems a promising methodology to automatically find programs to solve new computing challenges. The Evolutionary Programming techniques use classical genetic operators (selection, crossover and mutation) to automatically generate programs targeted to solve computing problems or specifications. Among the methodologies related with Evolutionary Programming we can find Genetic Programming, Analytic Programming and Grammatical Evolution. In this paper we present the Evolutionary Programming Multiagent Systems (EPMAS) framework based on Grammatical Evolution (GE) to evolutionary generate Multi-agent systems (MAS) ad-hoc. We also present two case studies in MAS scenarios for applying our EPMAS framework: the predator-prey problem and the Iterative Prisoner’s Dilemma.
منابع مشابه
Continuous On-line Evolution of Agent Behaviours with Cartesian Genetic Programming
Evolutionary Computation has been successfully used to synthesise controllers for embodied agents and multi-agent systems in general. Notwithstanding this, continuous on-line adaptation by the means of evolutionary algorithms is still under-explored, especially outside the evolutionary robotics domain. In this paper, we present an on-line evolutionary programming algorithm that searches in the ...
متن کاملConstruction of Cooperative Behavior in Multi-Agent Systems
Massive multi-agent systems with emergent global behavior represent a new paradigm in designing and building program systems for handling complex problems. Emergence, nonlinearity and self-organization of global behavior underpin robustness, flexibility and autonomy of massive multi-agent systems. On the other hand, this makes the traditional design approach difficult, if not impossible. In thi...
متن کاملA JADE-Based Framework for Developing Evolutionary Multi-Agent Systems
Evolutionary agents are flexible, agile, capable of learning, and appropriate for problems with changing conditions or where the correct solution cannot be known in advance. Evolutionary Multi-Agent systems, therefore, consist of populations of agents that learn through interactions with the environment and with other agents and which are periodically subject to evolutionary processes. In this ...
متن کاملEmergent Thought Automated Agent Design Mini-project Report
The following report presents the preliminary results and theoretical backgrounds of a multi-layer evolutionary mechanism. The project aims at developing a mechanism for automated agent design within a pre-designed multi-layer architecture. The core mechanism used in the experiments is a Genetic Programming algorithm working in a specially designed condition-action rules system. There is descri...
متن کاملMemetic Computing In Selected Agent-Based Evolutionary Systems
In the paper an application of selected agent-based evolutionary computing models, such as flock-based multi agent system (FLOCK) and evolutionary multi-agent system (EMAS), to the problem of continuous optimisation is presented. It turns out, that hybridizing of agent-based paradigm with evolutionary computation brings a new quality to the meta-heuristic field, easily enhancing static individu...
متن کامل