# Questions tagged [reinforcement-learning]

The tag has no usage guidance.

95 questions
Filter by
Sorted by
Tagged with
31 views

### How to distinguish between Unrepresentative Train Dataset and minimal overfitting from a learning c

Hi I saw a picture in a group and I asked to myself what exactly is this? Is this a minimal over fitting or like unpresensitive train dataset? However I read it on the net but still have problem in ...
1 vote
35 views

### DeepMind Alphadev: How did it use Reinforcement Learning to reduce the search space?

Google DeepMind recently published a new paper which describes how they used a reinforcement learning to discover faster sorting algorithms. A summary of the paper is here and the paper is here. It ...
22 views

### How to solve MAB by linear program?

To solve multi-armed bandit problem, the common approaches are UCB or TS and there are many variants of these algorithms. I am wondering if it is possible to model and solve this problem as a linear ...
9 views

### Role of State Dynamics Target Network in DDPG

I am trying to create a variant of DDPG in MATLAB that has no action-value $\langle Q \rangle$ net, but that instead works with networks $\langle V \rangle, \langle f \rangle, \langle r \rangle$, and ...
16 views

### Bellmann Error with Time Step

I define the return $G$ as the discrete time integral of the reward $G = \Delta t \sum_{t = 0, ..., T}r_t$. In supposing $\Delta t = 1$ throughout, my instructor wrote the following formula for the ...
78 views

### Multi-Armed Bandit - Reward Probabilities

I am new to reinforcement learning, and recently came across the following issue. When implementing a multi-armed bandit algorithm, we assume we have k machines with reward probabilities [p_1,..., p_k]...
1 vote
136 views

### Tabular Meta-Learning in RL

There are various meta-learning algorithms in RL that are proposed for settings when we have a (deep) neural network and the policy (or the value function) are parameterized as such. Can these methods ...
54 views

### Reinforcement Learning Reward Function for Optimizing Golf Aim?

I read this article, mentioning that either here, or StackOverflow would be the best places to ask generic machine learning questions, however, if the question isn't programming specific with a ...
1 vote
28 views

### Long and short memory in reinforcement learning Connect 4 AI

I'm writing an AI based on reinforcement learning to play Connect 4. That's my second bot and attempt to RNN and AI (first was copy a code of snake RNN AI from youtube) and I'm looking for some ...
1 vote
13 views

### Evaluating the safety of deep RL algorithms

Is there any free/open-source environment, tasks, or dataset for evaluating deep RL algorithms in terms of safety? all available environments (like openAI's) are environments for simple games. These ...
1 vote
36 views

### Deep RL for healthcare: existing benchmarking datasets or environments

I am currently a Ph.D. student in the computer science department, I was given the subject of Deep RL for Healthcare. However, after lots of research on the internet, I could not find any free dataset ...
29 views

### Where to find the current state of the art performance of Deep RL algorithms?

Recently, I had an idea of a novel Deep RL algorithm that might perform better than existing algorithms such as DQN, TRPO, PPO, etc. However, I do not know of a website or a research paper that might ...
65 views

### What makes Deep RL "fundamentally/mathematically" advantageous?

Note: I consider myself to be a beginner in the field of Deep RL. Deep RL has proven tremendous success in recent years like playing atari and beating go champion. Therefore, considerable interest for ...
813 views

### How to setup the Bellman Equation as a linear system of equation

I was watching a video on Reinforcement Learning by Andrew Ng, and at about minute 23 of the video he mentions that we can represent the Bellman equation as a linear system of equations. I am talking ...
26 views

### What is the relation between the compatibile features and the state features in Actor Critic Algorithm?

According to Actor-Critic algorithm, $\psi_{\theta}=\nabla_{\theta}\ln \mu_{\theta}(s, a)$ where $\mu_{\theta}(s, a)$ is the policy followed by the actor and $\psi_\theta$ is the compatibile features ...
1 vote
13 views

### Reinforcement learning with 0 rewards and costs

Suppose we have a hallway environment, i.e, $N$ nodes from left to right, and we can either move left or right. Moving left at the leftmost node does nothing and reaching the right most node gives you ...
8 views

### Inferring reward function and transition model from optimal policy

Consider an MDP where the transition model and the reward function are unknown. Consider an optimal policy $\pi^*$ generated from this MDP (say by some oracle who does know the transition model and ...
70 views

### Motivation for Inverse Reinforcement Learning

Learning a policy from sparse reward information (a reward function where a positive reward is only generated at the goal state) is challenging due to the resulting sparse feedback. One solution is to ...
26 views

### How to get best path from a set of path using Q-Learning?

I have 10 data sets (lat and long) of the same path. I started from point A and stopped in point B and did this 10 times for a single route to get the data. While collecting the data, there were some ...
1 vote
26 views

1 vote
34 views

### Why is the objective in a multi-armed bandit problems to minimize (cumulative) regret?

In a multi-armed bandit, the objective is to maximize the expected cumulative reward. This objective is usually (equivalently?) stated in terms of expected cumulative regret. Question: Why not just ...
1 vote
18 views

### How to compute the sample update error?

In the book Reinforcement Learning An Introduction，Chapter 8.5，there is an example that compares the efficiency of expected and sample updates: According to the author, "In this case, sample updates ...
1 vote
196 views

### Help needed for understanding proof of No Regret Multi Armed Bandit Algorithm

I was reading Elad Hazan's book on Online Convex Optimization(http://ocobook.cs.princeton.edu/OCObook.pdf) and am facing difficulty understanding the proof given for the No regret algorithm for MAB (...
1 vote
51 views

### What does actually happens on tile hashing

I am going through Richard Sutton book about Reinforcement Learning and I just encountered the tile coding method. I understood pretty well the principles, however, at the very end of the section, ...
761 views

### Understanding On-policy First Visit Monte Carlo Control algorithm

I am going through the Monte Carlo methods, and it's going fine until now. However, I am actually studying the On-Policy First Visit Monte Carlo control for epsilon soft policies, which allows us to ...
163 views

### (DROP) Data Reduction Algorithm - How it works?

I am studing a PHD framework which the propose is to reduce the dataset with the most representative samples for training a classifier. Maybe I am loosing something, but I could not undestand a ...
98 views

### Is the credit assignment problem a well-posed one?

Credit assignment is the process of assigning credit (or blame) to a particular move in a sequence of moves (temporal credit assignment) or to a particular node (structural credit assignment) among ...
1 vote
447 views

### Is deep learning appropriate to approximate dynamic programming problems?

I have a problem which can be completely solved using dynamic programming, but in a very intractable way (On^4, where n is around 1000). I won't get into the details of the problem since it's a bit ...