As we can see, the efficiency of our agent to solve an environment depends on what policy it uses to match state-action pairs at each time step. Hence, a function, known as a policy function (π), can specify the combination of state-action pairs for each time step the agent comes across. As the simulation runs, the policy is responsible for producing the trajectory, which is composed of game-states; actions that are taken by our agent as a response; and a reward that's generated by the environment, as well as the next state of the game the agent receives. Intuitively, you can think of a policy as a heuristic that generates actions that respond to the generated states of an environment. A policy function itself can be a good or a bad one. If your policy is to shoot first and ask questions later, you may end up shooting a hostage. Hence...
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You're reading from Hands-On Neural Networks with Keras
Niloy Purkait is a technology and strategy consultant by profession. He currently resides in the Netherlands, where he offers his consulting services to local and international companies alike. He specializes in integrated solutions involving artificial intelligence, and takes pride in navigating his clients through dynamic and disruptive business environments. He has a masters in Strategic Management from Tilburg University, and a full specialization in data science from Michigan University. He has advanced industry grade certifications from IBM, in subjects like signal processing, cloud computing, machine and deep learning. He is also perusing advanced academic degrees in several related fields, and is a self-proclaimed lifelong learner.
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Niloy Purkait is a technology and strategy consultant by profession. He currently resides in the Netherlands, where he offers his consulting services to local and international companies alike. He specializes in integrated solutions involving artificial intelligence, and takes pride in navigating his clients through dynamic and disruptive business environments. He has a masters in Strategic Management from Tilburg University, and a full specialization in data science from Michigan University. He has advanced industry grade certifications from IBM, in subjects like signal processing, cloud computing, machine and deep learning. He is also perusing advanced academic degrees in several related fields, and is a self-proclaimed lifelong learner.
Read more about Niloy Purkait