Abstract
Memetic multiagent system emerges as an enhanced version of multiagent systems with the implementation of meme inspired computational agents. It aims to evolve human-like behavior of multiple agents by exploiting the Dawkins’ notion of a meme and Universal Darwinism. Previous research has developed a computational framework in which a series of memetic operations have been designed for implementing human-like agents. This paper will focus on improving the human-like behavior of multiple agents when they are engaged in social interactions. The improvement is mainly on how an agent shall learn from others and adapt its behavior in a complex dynamic environment. In particular, we design a new mechanism that supervises how the agent shall select one of the other agents for the learning purpose. The selection is a trade-off between the elitist and like-attracts-like principles. We demonstrate the desirable interactions of multiple agents in two problem domains.
| Original language | English |
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| Number of pages | 8 |
| Publication status | Published - 2013 |
| Event | IEEE Congress on Evolutionary Computation - Fiesta Americana Grand Coral Beach Hotel, Cancun, Mexico Duration: 20 Jun 2013 → 23 Jun 2013 |
Conference
| Conference | IEEE Congress on Evolutionary Computation |
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| Country/Territory | Mexico |
| City | Cancun |
| Period | 20/06/13 → 23/06/13 |