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In this paper, we show that it is possible to use electroencephalography (EEG) and multi-brain computing with two humans to guide an Interactive Genetic Algorithm (IGA) system. We show that combining neural activity across two brains increases accuracy to guide evolutionary search more effectively. The IGA system involves a simple task of evolving a polygon shape to approximate the shape of a target...
In this paper we present a negotiation agent based on Genetic Algorithm (GA) and Surrogate Modelling for a multi-player multi-issue negotiation model under incomplete information scenarios to solve a resource-allocation problem. We consider a multi-lateral negotiation protocol by which agents make offers sequentially in consecutive rounds until the deadline is reached. Agents' offers represent suggestions...
This paper proposes a new technique based on Hyper Genetic Algorithm (GA) and Particle Swarm Optimisation (PSO) to evolve optimal agenda for bilateral multi-issue negotiation. In sequential negotiation the agenda specifies the set of issues included in the negotiation and the order in which they will be discussed. A player's profit from negotiation depends on the agenda. Each player wants to find...
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