# Questions tagged [reinforcement-learning]

For questions related to learning controlled by external positive reinforcement or negative feedback signal or both, where learning and use of what has been thus far learned occur concurrently.

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152 views

### Benchmarks for reinforcement learning in discrete MDPs

To compare the performance of various algorithms for perfect information games, reasonable benchmarks include reversi and m,n,k-games (generalized tic-tac-toe). For imperfect information games, ...
93 views

### What is the appropriate approach to playing a game with incomplete state information?

I have a steady hex-map and turn-based war game featuring WWII carrier battles. I would like to improve the fixed policy for the AI using reinforcement learning. I have some beginner's questions, ...
753 views

### Traveling salesman problem variant: which algorithm to choose?

I have an industrial problem which I'm trying to cast as a Traveling Salesman problem (TSP) in 3D euclidian space. There are physical limitations which implies that some subpaths may or may not be ...
102 views

### How are the reward functions $R(s)$, $R(s, a)$ and $R(s, a, s')$ equivalent?

In this video, the lecturer states that $R(s)$, $R(s, a)$ and $R(s, a, s')$ are equivalent representations of the reward function. Intuitively, this is the case, according to the same lecturer, ...
100 views

111 views

### What will Q-values look like in self-play tic-tac-toe?

This corresponds to Exercise 1.1 of RLBook, and a discussion followed from here. Considering two reward schemes- Win = +1, Draw = 0, Loss = -1 Win = +1, Draw or Loss = 0 Can we say something about ...
374 views

### Why is the reward signal normalized in openAI's REINFORCE?

Pytorch's example for the REINFORCE algorithm for reinforcement learning has the following code: ...
112 views

### Once the environments are vectorized, how do I have to gather immediate experiences for the agent?

My main purpose right now is to train an agent using the A2C algorithm to solve the Atari Breakout game. So far I have succeeded to create that code with a single agent and environment. To break the ...
66 views

### What happens if our target network overestimates the value?

When we use DDQN, we often use the target network in case our online network overestimates a value, but this doesn't make sense to me, because What happens if our target network is the one that ...
100 views

### Deep Q Learning Algorithm for Simple Python Game makes player stuck

I made a simple Python game. A screenshot is below: Basically, a paddle moves left and right catching particles. Some make you lose points while others make you gains points. This is my first Deep Q ...
635 views

### What is the difference between the epsilon greedy and softmax policies?

Could someone explain to me which is the key difference between the epsilon greedy policy and the softmax policy? In particular in the contest of SARSA and Q-Learning algorithms. I understood the main ...
229 views

### Importance of starting state and player in RL for Tic Tac Toe

So I am simulating a Tic Tac Toe game with a human opponent. The way the RL trains is through policy/value iterations for a fixed number of iterations all specified by the user. Now whether the human ...
99 views

### In RL, if I assign the rewards for better positional play, the algorithm is learning nothing?

I'm creating an RL application for the game Connect Four. If I tell the algorithm which moves/token positions will receive greater rewards, surely it's not actually learning anything; it's just a ...