Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Reinforcement learning (RL) is a method that helps programming an autonomous agent through human-like objectives as reinforcements, where the agent is responsible for discovering the best actions to fulfil the objectives. Nevertheless, it is not easy to disentangle human objectives in reinforcement like objectives. Inverse reinforcement learning (IRL) determines the reinforcements that a given agent behaviour is fulfilling from the observation of the desired behaviour.   present a variant of IRL, which is called IRL with evaluation (IRLE) where instead of observing the desired agent behaviour, the relative evaluation beten different behaviours is known by the access to an evaluator.  present also a solution for this problem under the assumption that a relative linear function that preserves the order assumed by the evaluator exists and that the evaluator evaluates policies instead of behaviours. This is posed as a linear feasibility problem, whose solution is ll known. Results of simulations of a set of heterogeneous robots in a search and rescue scenario are presented to illustrate the method and the possibility to transfer the learned reinforcement function among robots
['V. Freire da Silva', 'A.H. Reali Costa', 'P. Lima']
I am writing a research paper on a idea Inverse reinforcement learning with evaluation
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