A reinforcement learning update that adjusts each neuron's input-output sensitivity using TD error can replace external exploration noise and backpropagation through time in small actor-critic tasks.
Can I say, now machines can think?
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abstract
Generative AI techniques have opened the path for new generations of machines in diverse domains. These machines have various capabilities for example, they can produce images, generate answers or stories, and write codes based on the "prompts" only provided by users. These machines are considered 'thinking minds' because they have the ability to generate human-like responses. In this study, we have analyzed and explored the capabilities of artificial intelligence-enabled machines. We have revisited on Turing's concept of thinking machines and compared it with recent technological advancements. The objections and consequences of the thinking machines are also discussed in this study, along with available techniques to evaluate machines' cognitive capabilities. We have concluded that Turing Test is a critical aspect of evaluating machines' ability. However, there are other aspects of intelligence too, and AI machines exhibit most of these aspects.
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cs.LG 1years
2025 1verdicts
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Dynamic Reinforcement Learning for Actors
A reinforcement learning update that adjusts each neuron's input-output sensitivity using TD error can replace external exploration noise and backpropagation through time in small actor-critic tasks.