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Results tagged with reinforcement-learning
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user 36970
For questions related to reinforcement learning, i.e. a machine learning technique where we imagine an agent that interacts with an environment (composed of states) in time steps by taking actions and receiving rewards (or reinforcements), then, based on these interactions, the agent tries to find a policy (i.e. a behavioural strategy) that maximizes the cumulative reward (in the long run), so the goal of the agent is to maximize the reward.
1
vote
Accepted
Is it required that taking an action updates the state?
A very vague question. What's the objective?
Reinforcement Learning (RL) typically uses the Markov Decision Process framework, which is a sequential decision making framework. In this framework, acti …
- 56
3
votes
0
answers
96
views
Can we use a Gaussian process to approximate the belief distribution at every instant in a P...
Suppose $x_{t+1} \sim \mathbb{P}(\cdot | x_t, a_t)$ denotes the state transition dynamics in a reinforcement learning (RL) problem. Let $y_{t+1} = \mathbb{P}(\cdot | x_{t+1})$ denote the noisy observa …
- 56