The tag has no usage guidance.

learn more… | top users | synonyms

1
vote
0answers
13 views

single agent vs multiple agent reinforcement learning

I am confused about 'single' vs 'multiple' agent reinforcement learning. Let's say that I have 1 hunter who I am training to hunt 1 static prey, so that only the hunter is moving around. This is ...
3
votes
0answers
45 views

Reinforcement Learning - Agent training

In RL, in a game situation, usually the agent is trained by playing against itself. When we should not depend on this self-training, and switch to train the agent with a real or different player ...
0
votes
0answers
10 views

Memory storage capacity of Bienenstock-Cooper-Munro rule

I would like to know the memory storage capacity of the BCM learning rule when it is implemented on a Hopfield network. I understand that it will be a function of n where n is the number of neurons.
1
vote
1answer
28 views

Combining Production Rules using Reinforcement Learning

Production systems have been used to solve puzzles such as the Tower of Hanoi for years with hard-coded production rules. However, has there been any research in using reinforcement learning to ...
5
votes
1answer
44 views

The meaning of discount factor on reinforcement learning

After reading of the google deepmind achievements on Atari's games, I am trying to understand the q-learning and q-networks, but I am little bit confused. The confusion arise in the concept of the ...
0
votes
0answers
8 views

Reward function equivalence classes

Background: I have a reinforcement learning problem in which agents are learning how to interpret the knowledge given to them by other agents. The details of how they do this are a bit involved so ...
1
vote
0answers
24 views

How to determine convergence when using Q-learning?

I'm using Q-Learning to find the values of states in on a gameboard. For example, something like: ...
1
vote
0answers
31 views

How does SARSA handle episode termination

When applied to domains that are episodic and have a "final" state but no final action, like a game, how does SARSA update the Q-values? e.g. A game agent would receive this series: ...
3
votes
1answer
146 views

What's the difference between Adaptive Control and Hierarchical Reinforcement Learning?

After watching Travis DeWolf presentation on scaling neural computation, I'm a bit confused about the difference between Reinforcement Learning (whether hierarchical or not) and Adaptive Control. They ...
2
votes
0answers
31 views

Reinforcement learning - state space and action space

I am working on a reinforcement learning strategy for parameter control of a local search heuristic. The complete state for this RL problem can be defined as $S = \{s, p\}$, where $s$ and $p$ ...
3
votes
1answer
92 views

Why does ε-greedy $Q$-learning not oscillate?

I have a intuitive question on the convergence of $Q$- learning. In $Q$ learning for each step a $Q$- value is learned for the state-action pair where the action is selected according to the ...
2
votes
1answer
145 views

Q-learning in a Dynamic environment

I am new to reinforcement learning. Lately, I have learned Q-learning using the following tutorial. Is Q-learning still possible if the environment is dynamic. Using the environment of the tutorial ...