conversation_id int64 0 999 | messages listlengths 2 2 |
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600 | [
{
"context": "Are filters fixed or learned? No matter what I google or what paper I read, I can't find an answer to my question. In a deep convolutional neural network, let's say AlexNet (Krizhevsky, 2012), filters' weights are learned by means of back-prop.\nBut how are kernels themselves selected? I know kern... |
601 | [
{
"context": "When to expand and when to simulate in Monte Carlo Tree Search? In Monte Carlo Tree Search (MCTS), we start at root node $R$. Then we select some leaf node $L$. And we expand $L$ by one or more child nodes and simulate from the child to the end of the game. \n\nWhen should we expand and when shoul... |
602 | [
{
"context": "What are the state-of-the-art approaches for continual learning with neural networks? There seems to be a lot of literature and research on the problems of stochastic gradient descent and catastrophic forgetting, but I can't find much on solutions to perform continual learning with neural network ... |
603 | [
{
"context": "Can I use AI to interpret XML documents? I think about a system which gets XML documents in various structures but with essentially the same data structure in it. For the example, let's assume each document contains data about one or more persons. So the AI would recognize a name. Somewhere else i... |
604 | [
{
"context": "My Deep Q-Learning Network does not learn for OpenAI gym's cartpole problem I am implementing OpenAI gym's cartpole problem using Deep Q-Learning (DQN). I followed tutorials (video and otherwise) and learned all about it. I implemented a code for myself and I thought it should work, but the agent ... |
605 | [
{
"context": "How to improve the reward signal when the rewards are sparse? In cases where the reward is delayed, this can negatively impact a models ability to do proper credit assignment. In the case of a sparse reward, are there ways in which this can be negated?\nIn a chess example, there are certain moves ... |
606 | [
{
"context": "Why does ChatGPT create fake code? ChatGPT has been a big thing lately. It also makes a lot of mistakes. For example, it creates fake functions of a package and tells it as it works for real. I was wondering how that works. Why is it creating fake functions of code and not just telling that it doe... |
607 | [
{
"context": "Is it possible to make a 'forked path' neural network? I want to make a network, specifically a CNN for image recognition, that takes an input, processes it the same way for several layers, and then at some point splits before coming to two different outputs. Is it possible to create a network suc... |
608 | [
{
"context": "Is there a machine learning algorithm to find similar sales patterns? I have a dataset as follows\n\n(and the table extends to include an extra 146 columns for companies 4-149)\nIs there an algorithm I could use effectively to find similar patterns in sales from the other companies when compared t... |
609 | [
{
"context": "Why can't the XOR linear inseparability problem be solved with one perceptron like this? Consider a perceptron where $w_0=1$ and $w_1=1$:\n\nNow, suppose that we use the following activation function\n\\begin{align}\nf(x)=\n\\begin{cases}\n1, \\text{ if }x =1\\\\\n0, \\text{ otherwise}\n\\end{case... |
610 | [
{
"context": "How to shorten the development time of a neural network? I am developing an LSTM for sequence tagging. During the development, I do various changes in the system, for example, add new features, change the number of nodes in the hidden layers, etc. After each change, I check the accuracy using cro... |
611 | [
{
"context": "Why did the openai's gym website close? Openai's gym website redirects to the GitHub repository. Why did the openai's gym website close?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"context": "According to Open AI's Greg Brockman, the Gym ... |
612 | [
{
"context": "How can we prevent AGI from doing drugs? I recently read some introductions to AI alignment, AIXI and decision theory things.\nAs far as I understood, one of the main problems in AI alignment is how to define a utility function well, not causing something like the paperclip apocalypse.\nThen a que... |
613 | [
{
"context": "What is the difference between out of distribution detection and anomaly detection? I'm currently reading the paper Likelihood Ratios for Out-of-Distribution Detection, and it seems that their problem is very similar to the problem of anomaly detection. More precisely, given a neural network train... |
614 | [
{
"context": "Can two admissable heuristics not dominate each other? I am working on a project for my artificial intelligence class. I was wondering if I have 2 admissible heuristics, A and B, is it possible that A does not dominate B and B does not dominate A? I am wondering this because I had to prove if eac... |
615 | [
{
"context": "Can CNNs be applied to non-image data, given that the convolution and pooling operations are mainly applied to imagery? When using CNNs for non-image (times series) data prediction, what are some constraints or things to look out for as compared to image data?\nTo be more precise, I notice there a... |
616 | [
{
"context": "Is it suitable to find inverse of last layer's activation function and apply it on the target output? I have a neural network with the following structure:\n\nI am expecting specific outputs from the neural network which are the target values for my training. Let's say the target values are 0.8 fo... |
617 | [
{
"context": "Will a CNN that is Group Equivariant always be better than a regular CNN? I am reading this paper about Group Equivariant Convolutional Networks. Basically, it is a CNN whose construction makes the network naturally equivariant to Group transformations (e.g. rotations) of the input.\nThis is, a GE... |
618 | [
{
"context": "Can reinforcement learning algorithms be applied to computer vision problems? Can reinforcement learning algorithms be applied to computer vision problems? If yes, what are some examples of these applications?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null... |
619 | [
{
"context": "What is the difference between local search and global search algorithms? What is the difference between local search and global (or complete) search algorithms?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"context": "The difference between... |
620 | [
{
"context": "What are the pros and cons of sparse and dense rewards in reinforcement learning? From what I understand, if the rewards are sparse the agent will have to explore more to get rewards and learn the optimal policy, whereas if the rewards are dense in time, the agent is quickly guided towards its lea... |
621 | [
{
"context": "How can I create an artificially intelligent aimbot for a game like CS:GO? How can I create an artificially intelligent aimbot for a game like Counter-Strike Global Offensive (CS:GO)?\nI have an initial solution (or approach) in mind. We can train an image recognition model that will recognize the... |
622 | [
{
"context": "What are the real-life applications of transfer learning? What are the real-life applications of transfer learning in machine learning? I am particularly interested in industrial applications of the concept.\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
... |
623 | [
{
"context": "Does using the softmax function in Q learning not defeat the purpose of Q learning? It is my understanding that, in Q-learning, you are trying to mimic the optimal $Q$ function $Q*$, where $Q*$ is a measure of the predicted reward received from taking action $a$ at state $s$ so that the reward is ... |
624 | [
{
"context": "Why did a Tesla car mistake a truck with a bright sky? Do we know why Tesla's autopilot mistaken empty sky with a high-sided lorry which resulted in fatal crash involving a car in self-drive mode? Was it AI fault or something else? Is there any technical explanation behind this why this happened?\... |
625 | [
{
"context": "What is the difference between imitation learning and classification done by experts? In short, imitation learning means learning from the experts. Suppose I have a dataset with labels based on the actions of experts. I use a simple binary classifier algorithm to assess whether it is good expert a... |
626 | [
{
"context": "How to add more features to the input of a machine learning algorithm? I am trying to perform a binary classification of tweets using machine learning. \nThe usual way of doing this seems to be putting a hand-classified tweet's words into a big vector, then use that vector as input to an algorithm... |
627 | [
{
"context": "Why is AI safety so much harder than Isaac Asimov's \"Three Laws of Robotics\"? I understand that AI researchers are trying to create AI designs that allow for desired behavior without undesirable side-effects. A classic example of an attempt is Isaac Asimov's Three Laws of Robotics. This idea see... |
628 | [
{
"context": "What does the number of required expert demonstrations in Imitation Learning depend on? I just read the following points about the number of required expert demonstrations in imitation learning, and I'd like some clarifications. For the purpose of context, I'll be using a linear reward function th... |
629 | [
{
"context": "Why is the derivative of this objective function 0 if the policy is deterministic? In the Berkeley RL class CS294-112 Fa18 9/5/18, they mention the following gradient would be 0 if the policy is deterministic.\n$$\n\\nabla_{\\theta} J(\\theta)=E_{\\tau \\sim \\pi_{\\theta}(\\tau)}\\left[\\left(\\s... |
630 | [
{
"context": "How can the policy iteration algorithm be model-free if it uses the transition probabilities? I'm actually trying to understand the policy iteration in the context of RL. I read an article presenting it and, at some point, a pseudo-code of the algorithm is given : \nWhat I can't understand is this... |
631 | [
{
"context": "What is \"planning\" in the context of reinforcement learning, and how is it different from RL and SL? This is an excerpt taken from Sutton and Barto (pg. 3):\n\nAnother key feature of reinforcement learning is that it explicitly considers the whole problem of a goal-directed agent interacting wit... |
632 | [
{
"context": "Clarifying representation of Neural Nerwork input for Chess Alpha Zero In the Alpha Zero paper (https://arxiv.org/pdf/1712.01815.pdf) page 13, the input for the NN is described. In the beggining of the page, the authors state that:\n\"The input to the Neural Network is an N x X x (MT + L) image st... |
633 | [
{
"context": "When to use Value Iteration vs. Policy Iteration Both value iteration and policy iteration are General Policy Iteration (GPI) algorithms. However, they differ in the mechanics of their updates. Policy Iteration seeks to first find a completed value function for a policy, then derive the Q functi... |
634 | [
{
"context": "In MCTS, what to do if I do not want to simulate till the end of the game? I'm trying to implement MCTS with UCT for a board game and I'm kinda stuck. The state space is quite large (3e15), and I'd like to compute a good move in less than 2 seconds. I already have MCTS implemented in Java from her... |
635 | [
{
"context": "What is the role of the hidden vectors in restricted Boltzmann machines? I'm learning about the restricted Boltzmann machine (RBM), and I just came up with two naive understandings of this model. But it seems these two understandings are so different.\nMy first understanding goes like this.\nThe ... |
636 | [
{
"context": "If the current state is $S_t$ and the actions are chosen according to $\\pi$, what is the expectation of $R_{t+1}$ in terms of $\\pi$ and $p$? I'm trying to solve exercise 3.11 from the book Sutton and Barto's book (2nd edition)\n\nExercise 3.11 If the current state is $S_t$ , and actions are sele... |
637 | [
{
"context": "What does \"hard for AI\" look like? In theoretical computer science, there is a massive categorization of the difficulty of various computational problems in terms of their asymptotic worst-time computational complexity. There doesn't seem to be any analogous analysis of what problems are \"hard ... |
638 | [
{
"context": "When to use the state value function $V(s)$ and when to use the state-action value function $Q(s, a)$? I saw the difference between value function $V(s)$ and $Q(s, a)$. But when do I use each one? When I coded in Matlab I only used $Q(s, a)$ directly (as I was thinking of a tabular approach). So, ... |
639 | [
{
"context": "How to express a fully connected neural network succintly using linear algebra? I'm currently reading the paper Federated Learning with Matched Averaging (2020), where the authors claim:\n\nA basic fully connected (FC) NN can be formulated as: $\\hat{y} = \\sigma(xW_1)W_2$ [...]\nExpanding the pre... |
640 | [
{
"context": "Why is tf.abs non-differentiable in Tensorflow? I understand why tf.abs is non-differentiable in principle (discontinuity at 0) but the same applies to tf.nn.relu yet, in case of this function gradient is simply set to 0 at 0. Why the same logic is not applied to tf.abs? Whenever I tried to use it... |
641 | [
{
"context": "What is a weighted average in a non-stationary k-armed bandit problem? In the book Reinforcement Learning: An Introduction (page 25), by Richard S. Sutton and Andrew G. Barto, there is a discussion of the k-armed bandit problem, where the expected reward from the bandits changes slightly over time... |
642 | [
{
"context": "Why are only neural networks (and not SVMs, for example) used for reinforcement learning? I know that neural networks are the \"universal function approximator\", but they also have a huge number of trainable parameters and are extremely prone to overfitting.\nSo my question is: Why aren't SVMs or... |
643 | [
{
"context": "Does the quality of training images affect the accuracy of the neural network? I just got into AI few months ago. I noticed most of the images in training datasets are usually low quality( almost pixelated). \nDoes the quality of training images affect the accuracy of the neural network? \nI tried... |
644 | [
{
"context": "Can TD($\\lambda$) be used with deep reinforcement learning? TD lambda is a way to interpolate between TD(0) - bootstrapping over a single step, and, TD(max), bootstrapping over the entire episode length, or, Monte Carlo.\nReading the link above, I see that an eligibility trace is kept for each st... |
645 | [
{
"context": "How do I design a neural network that breaks a 5-letter word into its corresponding syllables? I am going to design a neural network which will be able to break a 5-letter word into its corresponding syllables (hybrid syllables, I mean it will not strictly adhere to grammatical syllable rules but ... |
646 | [
{
"context": "What is the difference between a language model and a word embedding? I am self-studying applications of deep learning on the NLP and machine translation.\nI am confused about the concepts of \"Language Model\", \"Word Embedding\", \"BLEU Score\".\nIt appears to me that a language model is a way t... |
647 | [
{
"context": "Which paper introduced the term \"softmax\"? Nowadays, the softmax function is widely used in deep learning and, specifically, classification with neural networks. However, the origins of this term and function are almost never mentioned anywhere. So, which paper introduced this term?\n",
"ima... |
648 | [
{
"context": "When should we use algorithms like Adam as opposed to SGD? As far as I know, Stochastic Gradient Descent is an optimization algorithm which belongs to the the category of algorithms where hyper-parameters have to be defined beforehand. They are useful in many cases, but there are some cases that t... |
649 | [
{
"context": "Why don't we use auto-encoders instead of GANs? I have watched Stanford's lectures about artificial intelligence, I currently have one question: why don't we use autoencoders instead of GANs?\nBasically, what GAN does is it receives a random vector and generates a new sample from it. So, if we tra... |
650 | [
{
"context": "Why is exploitation necessary during training? I have read many blog articles making all kinds of broad analogies to explain the exploration/exploitation trade-off. However, I still can't fully grasp it. On an extremely abstract level, I understand why you would want to \"try new things to gain in... |
651 | [
{
"context": "Is there any artificially intelligent system that really mimics human intelligence? After having read something that Elon Musk said about artificial intelligence and how it could affect our lives, I've been reading about artificial intelligence, deep learning, etc. The recurrent topic is neural ne... |
652 | [
{
"context": "What is the relationship between robustness and adversarial machine learning? I have been reading a lot of articles on adversarial machine learning and there are mentions of \"best practices for robust machine learning\". \nA specific example of this would be when there are references to \"loss of... |
653 | [
{
"context": "Feasibility of generating large images with a convnet I've spent the past couple of months learning about neural networks, and am thinking of projects that would be fun to work on to cement my understanding of this tech.\nOne thing that came to mind last night is a system that takes an image of a ... |
654 | [
{
"context": "Why not more TD(𝜆) in actor-critic algorithms? Is there either an empirical or theoretical reason that actor-critic algorithms with eligibility traces have not been more fully explored? I was hoping to find a paper or implementation or both for continuous tasks (not episodic) in continuous state-... |
655 | [
{
"context": "Why is the denominator ignored in the Bayes' rule? The naïve Bayes' generative algorithm is often represented by the following formula:\n$$\\text{argmax}_{y} p(y|x) = \\text{argmax}_y \\frac{p(x|y)p(y)}{p(x)} \\approx \\text{argmax}_y p(x|y)p(y)$$\nWhy do we have $p(x)=1$ which allows the approxim... |
656 | [
{
"context": "What is the difference between artificial intelligence and swarm intelligence? Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits ... |
657 | [
{
"context": "Is it better to make neural network to have hierchical output? i'm quite new to neural network and i recently built neural network for number classification in vehicle license plate. It has 3 layers: 1 input layer for 16*24(382 neurons) number image with 150 dpi , 1 hidden layer(199 neurons) with ... |
658 | [
{
"context": "Is a Sobel filter for edge detection a type of Cellular Neural Network? I have implemented a Sobel filter for edge detection in Matlab without using its toolbox. I am a bit confused: \nIs a Sobel filter a type of Cellular Neural Network?\nBoth Sobel and Cellular Neural Network calculate output via... |
659 | [
{
"context": "Why are GRU and LSTM better than standard RNNs? It seems that older RNNs have a limitation for their use cases and have been outperformed by other recurrent architectures, such as the LSTM and GRU.\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
... |
660 | [
{
"context": "Does ChatGPT type slowly on purpose or is it computing? When you give ChatGPT a prompt, does it\nA) generate the entire response instantly (at least on the server), but then \"buffers\" it slowly to the end user (for whatever reason)\nor\nB) it's actually generating words (and sometimes entire sen... |
661 | [
{
"context": "What are the state space and the state transition function in AI? I'm studying for my AI final exam, and I'm stuck in the state space representation. I understand initial and goal states, but what I don't understand is the state space and state transition function. Can someone explain what are the... |
662 | [
{
"context": "How does A* search work given there are multiple goal states? When I have read through the fundamentals of AI, I saw a situation (i.e., a search space) which is illustrated in the following picture.\n\nThese are the heuristic estimates:\nh(B)=9\nh(D)=10\nh(A)=2\nh(C)=1\n\nIf we use the A* algorith... |
663 | [
{
"context": "Would convolutional NN recognize patterns in encoded images? I have a set of images that I already trained a CNN to classify successfully. I wonder if it would be possible to encode the images (using XOR in combination with a key of the same length as the image) and train a new net on them. \nThin... |
664 | [
{
"context": "What is the loss for policy gradients with continuous actions? I know with policy gradients used in an environment with a discrete action space are updated with $$\n\\Delta \\theta_{t}=\\alpha \\nabla_{\\theta} \\log \\pi_{\\theta}\\left(a_{t} \\mid s_{t}\\right) v_{t}\n$$\nwhere $v_t$ could be ma... |
665 | [
{
"context": "How does Lucas's argument work? In Minds, Machines and Gödel (1959), J. R. Lucas shows that any human mathematician can not be represented by an algorithmic automaton (a Turing Machine, but any computer is equivalent to it by the Church-Turing thesis), using Gödel's incompleteness theorem.\nAs I u... |
666 | [
{
"context": "What techniques are used to make MDP discrete state space manageable? Generating a discretized state space for an MDP (Markov Decision Process) model seems to suffer from the curse of dimensionality.\nSupposed my state has a few simple features:\n\nFeeling: Happy/Neutral/Sad\nFeeling: Hungry/Neith... |
667 | [
{
"context": "Is random initialization of the weights the only choice to break the symmetry? My knowledge\nSuppose you have a layer that is fully connected, and that each neuron performs an operation like\na = g(w^T * x + b)\n\nwere a is the output of the neuron, x the input, g our generic activation function, ... |
668 | [
{
"context": "Do Vision Transformers handle arbitrary sequence lengths the same way as normal Transformers? Does ViT do handle arbitrary sequence lengths using masking the same way the normal Transformer does?\nThe ViT paper doesn't mention anything about it, so I assume it uses masking like the normal Transfor... |
669 | [
{
"context": "Is it possible to create LLM using NEAT or its variations? While researching neuroevolutionary algorithms, neural networks performed well on a variety of tasks, creating complex systems. But when I needed something more complex, trying to create a GenAI for text or a simple translator between two ... |
670 | [
{
"context": "What is the goal of weight initialization in neural networks? This is a simple question. I know the weights in a neural network can be initialized in many different ways like: random uniform distribution, normal distribution, and Xavier initialization. But what is the weight initialization trying ... |
671 | [
{
"context": "Current limitations to artificial consciousness With some knowledge of machine learning and deep learning, it seems very unlikely for AI to develop into the consciousness that we imagine.\nTo me, consciousness requires a new framework that is very different from what we have today, as current form... |
672 | [
{
"context": "Why do my rewards reduce after extensive training using D3QN? I am running a drone simulator for collision avoidance using a slight variant of D3QN. The training is usually costly (runs for at least a week) and I have observed that reward function gradually increases during training and then drast... |
673 | [
{
"context": "How to write a C decompiler using AI? I would like to learn more about whether it is possible and how to write a program that decompiles executable binary (an object file) to the C source. I'm not asking exactly 'how', but rather how this can be achieved.\nGiven the following hello.c file (as exam... |
674 | [
{
"context": "Formal definition of the Object Detection problem For many problems in computer science, there is a formal, mathematical problem defition.\nSomething like: Given ..., the problem is to ...\nHow can the Object Detection problem (i.e. detecting objects on an image) be formally defined?\nGiven a set ... |
675 | [
{
"context": "Does AI rely on determinism? I don’t believe in free will, but most people do. Although I’m not sure how an act of free will could even be described (let alone replicated), is libertarian freewill something that is considered for AI? Or is AI understood to be deterministic?\n",
"images": null,... |
676 | [
{
"context": "If vanishing gradients are NOT the problem that ResNets solve, then what is the explanation behind ResNet success? I often see blog posts or questions on here starting with the premise that ResNets solve the vanishing gradient problem.\nThe original 2015 paper contains the following passage in sec... |
677 | [
{
"context": "Why don't we train highly specialized, highly polished, single knowledge LLMs? LLMs are trained on astronomical amounts of data, but it doesn't appear to have occurred to anyone to train highly specialized, highly polished, single knowledge LLMs, such as the ones listed below, orchestrated as a se... |
678 | [
{
"context": "What is the “Hello World” problem of Unsupervised Learning? As a followup to this question, I'm interested in what the typical \"Hello World\" problem (first easy example problem) is for unsupervised learning.\nA quick Google search didn't find any obvious answers for me.\n",
"images": null,
... |
679 | [
{
"context": "How is the gradient of the loss function in DQN derived? In the original DQN paper, page 1, the loss function of the DQN is\n$$\nL_{i}(\\theta_{i}) = \\mathbb{E}_{(s,a,r,s') \\sim U(D)} [(r+\\gamma \\max_{a'} Q(s',a',\\theta_{i}^{-}) - Q(s,a;\\theta_{i}))^2]\n$$\nwhose gradient is presented (on p... |
680 | [
{
"context": "Interesting examples of discrete stochastic games SGs are a generalization of MDPs to multiple agents. Like this previous question on MDPs, are there any interesting examples of zero-sum, discrete SGs—preferably with small state and action spaces? I'm hoping to use such examples as benchmarks, but... |
681 | [
{
"context": "How does the uniform-cost search algorithm work? What is the uniform-cost search (UCS) algorithm? How does it work? I would appreciate seeing a graphical execution of the algorithm. How does the frontier evolve in the case of UCS?\n",
"images": null,
"role": "user",
"thinking": null,
... |
682 | [
{
"context": "Reward interpolation between MDPs. Will an optimal policy on both ends stay optimal inside the interval? Say I've got two Markov Decision Processes (MDPs):\n$$\\mathcal{M_0} = (\\mathcal{S}, \\mathcal{A}, P, R_0),\\quad\\text{and}\\quad\\mathcal{M}_1 = (\\mathcal{S}, \\mathcal{A}, P, R_1)$$\nBoth ... |
683 | [
{
"context": "Which nodes are expanded in the expansion phase of MCTS? I'm confused regarding a specific detail of MCTS.\nTo illustrate my question, let's take the simple example of tic-tac-toe.\nAfter the selection phase, when a leaf node is reached, the tree is expanded in the so-called expansion phase. Let's... |
684 | [
{
"context": "Given enough computational resources, do we currently have any algorithms which could achieve AI? Hypothetically, assume that you have access to infinite computing power. Do we have designs for any brute-force algorithms that can find an AI capable of passing traditional tests (e.g. Turing, Chines... |
685 | [
{
"context": "What are the differences in scope between statistical AI and classical AI? What are the differences in scope between statistical AI and classical AI?\nReal-world examples would be appreciated.\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"co... |
686 | [
{
"context": "What exactly are partially observable environments? I have trouble understanding the meaning of partially observable environments. Here's my doubt.\nAccording to what I understand, the state of the environment is what precisely determines the next state and reward for any particular action taken. ... |
687 | [
{
"context": "What are the advantages of the Kullback-Leibler over the MSE/RMSE? I've recently encountered different articles that are recommending to use the KL divergence instead of the MSE/RMSE (as the loss function), when trying to learn a probability distribution, but none of the articles are giving a clea... |
688 | [
{
"context": "How do I know when to use which Monte Carlo method? I'm a bit confused with extensive number of different Monte Carlo methods such as:\n\nHamiltonian/Hybrid Monte Carlo (HMC),\nDynamic Monte Carlo (DMC),\nMarkov chain Monte Carlo (MCMC),\nKinetic Monte Carlo (KMC),\nDynamic Monte Carlo (DMC)\nQuas... |
689 | [
{
"context": "Can this tic tac toe program be considered AI? I coded a tic tac toe program, but I don't know if I can call it artificial intelligence.\nHere's what I did.\nThere is a random player, which always makes random valid moves.\nAnd then there is the AI player, which will receive input before every mov... |
690 | [
{
"context": "What is the effect of parallel environments in reinforcement learning? Do parallel environments improve the agent's ability to learn or does it not really make a difference? Specifically, I am using PPO, but I think this applies across the board to other algorithms too.\n",
"images": null,
... |
691 | [
{
"context": "What algorithm to use for completely randomized pokemon battles? I'm currently playing around with a pokemon battle simulator where the pokemon's stats & abilities and movesets are completely randomized. Each move itself is also completely randomized (meaning that you can have moves with 100 power... |
692 | [
{
"context": "What is the probability of selecting the greedy action in a 0.5-greedy selection method for the 2-armed bandit problem? I'm new to reinforcement learning and I'm going through Sutton and Barto. Exercise 2.1 states the following:\n\nIn $\\varepsilon$-greedy action selection, for the case of two act... |
693 | [
{
"context": "What is the difference between policy and action in reinforcement learning? I'm confused with the two terminology - action and policy - in Reinforcement Learning. As far as I know, the action is:\n\nIt is what the agent makes in a given state.\n\nHowever, the book I'm reading now (Hands-On Reinfor... |
694 | [
{
"context": "Does a neural network exist that can learn every possible training data? The universal approximation theorem states, that a feed-forward network with a single hidden layer containing a finite number of neurons can approximate continuous functions on compact subsets of $R^n$.\nMichael Nielsen state... |
695 | [
{
"context": "Is there a logical method of deducing an optimal batch size when training a Deep Q-learning agent with experience replay? I am training an RL agent using Deep-Q learning with experience replay. At each frame, I am currently sampling 32 random transitions from a queue which stores a maximum of 2000... |
696 | [
{
"context": "Which situation will helpful using encoder or decoder or both in transformer model? I have some questions about using (encoder / decoder / encoder-decoder) transformer models, included (language) transformer or Vision transformer.\nThe overall form of a transformer consists of an encoder and a dec... |
697 | [
{
"context": "In NEAT, is it a good idea to give the same ID to node genes created from the same connection gene? Do I have to prevent nodes created from the same connection gene to have different IDs/innovation number? In this example, the node 6 is created from the connection going from node 3 to node 4:\n\nI... |
698 | [
{
"context": "What is the formula used to calculate the loss in the FaceNet model? The FaceNet model returns the loss of the predictions and ground-truth classes. How is this loss calculated?\n",
"images": null,
"role": "user",
"thinking": null,
"tool_calls": null
},
{
"context": "The lo... |
699 | [
{
"context": "Why are neural networks preferred to other classification functions optimized by gradient decent Consider a neural network, e.g. as presented by Nielsen here. Abstractly, we just construct some function $f: \\mathbb{R}^n \\to [0,1]^m$ for some $n,m \\in \\mathbb{N}$ (i.e. the dimensions of the inp... |
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