Abstract
We propose a self-generating algorithm of behavioral evaluation that is important for a learning function in order to develop appropriate cooperative behavior among robots depending on the situation. The behavioral evaluation is composed of rewards and a consumption of energy. Rewards are provided by an operator when the robots share tasks appropriately, and the consumption of energy is measured during the execution of the tasks. Each robot estimates rules of behavior selection by using the evaluation generated, and learns to select an appropriate behavior when it meets the same situation. As a result, the robots may be able to share tasks efficiently even if the purpose of their task is changed by an operator in the middle of execution, because the evaluation is modified depending on the situation. We performed simulations to study the effectiveness of the proposed algorithm. In the simulations, we applied the algorithm to three robots, each with three behaviors. We confirmed that each robot can generate an appropriate behavioral evaluation based on rewards from an operator, and therefore they develop cooperative behaviors such as task sharing.
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Ohkawa, K., Shibata, T. & Tanie, K. Self-generating algorithm of evaluation for cooperative behavior. Artificial Life and Robotics 2, 138–143 (1998). https://doi.org/10.1007/BF02471171
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DOI: https://doi.org/10.1007/BF02471171