Robots that Reason

As such, it seems likely that developments in model based reinforcement learning are likely to constitute the next wave of advancements in the field of artificial intelligence..Already DeepMind has made some impressive progress towards that goal with the introduction of algorithms for “Relational Deep Reinforcement Learning”..These combine relational networks with reinforcement learning, allowing an agent to speculate about how objects in the environment interact with its actions to produce desirable results.In many ways this shift to model based reinforcement learning recapitulates the evolution of acquired cultural strategies in humans..Consider modern agriculture — as Jared Diamond points out in his book “The Third Chimpanzee”, this likely began as an entirely unconscious process occurring as humans gathered wild plants, in the process, unwittingly depositing seeds near their domestic enclosures..Some of these seeds would later have sprouted, giving rise to the first proto-gardens..Thus an unconscious model free strategy could gradually have given rise to a conscious model based one as humans took to weeding, harvesting and replanting those once wild plants..With Relational Deep Reinforcement Learning, it could be argued that computers are undergoing a similar “great leap forward”, transitioning from model free reinforcement learning strategies to ones that use models to reason and conjecture about their environments.The upshot is that human culture, the collective knowledge of our species that can be transferred and improved upon, may soon have a corollary within computer science and robotics..Relational networks developed by a deep RL agent can gradually be improved upon, and then broadcast out to other agents..This, in theory, allows multiple agents to slowly improve their collective understanding of a given environment in a similar way to the method in which human scientific knowledge grew over time, engendering among other things, the civilization in which we presently live.. More details

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