Bibliography:

‘RL’ tag
‘data pruning’ tag
‘active learning’ tag
‘NN sampling’ tag
‘novelty U-curve’ tag
‘hidden-information game’ tag
‘MARL’ tag
‘Nethack AI’ tag
‘robotics’ tag
Benchmarking LLM Diversity & Creativity
Can You Unsort Lists for Diversity?
Number Search Engine via NN Embeddings
Novelty Nets: Classifier Anti-Guidance
Free-Play Periods for RL Agents
Candy Japan’s new box A/B test
SimpleStrat: Diversifying Language Model Generation with Stratification
Learning Formal Mathematics From Intrinsic Motivation
Intelligent Go-Explore (IGE): Standing on the Shoulders of Giant Foundation Models
Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts
Self-Supervised Behavior Cloned Transformers are Path Crawlers for Text Games
Zero-Shot Goal-Directed Dialogue via RL on Imagined Conversations
QDAIF: Quality-Diversity through AI Feedback
Beyond Memorization: Violating Privacy Via Inference with Large Language Models
Let Models Speak Ciphers: Multiagent Debate through Embeddings
Small batch deep reinforcement learning
Language Reward Modulation for Pretraining Reinforcement Learning
Diversifying AI: Towards Creative Chess with AlphaZero (AZ_db)
Supervised Pretraining Can Learn In-Context Reinforcement Learning
Learning to Generate Novel Scientific Directions with Contextualized Literature-based Discovery
You And Your Research
Long-Term Value of Exploration: Measurements, Findings and Algorithms
Inducing anxiety in GPT-3.5 increases exploration and bias
Reflexion: Language Agents with Verbal Reinforcement Learning
MimicPlay: Long-Horizon Imitation Learning by Watching Human Play
MarioGPT: Open-Ended Text2Level Generation through Large Language Models
DreamerV3: Mastering Diverse Domains through World Models
AlphaZe∗∗: AlphaZero-like baselines for imperfect information games are surprisingly strong
Effect of lysergic acid diethylamide (LSD) on reinforcement learning in humans
Curiosity in hindsight
In-context Reinforcement Learning with Algorithm Distillation
E3B: Exploration via Elliptical Episodic Bonuses
Vote-K: Selective Annotation Makes Language Models Better Few-Shot Learners
LGE: Cell-Free Latent Go-Explore
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning
Trajectory Autoencoding Planner: Efficient Planning in a Compact Latent Action Space
Value-free random exploration is linked to impulsivity
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling
The cost of information acquisition by natural selection
Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos
BYOL-Explore: Exploration by Bootstrapped Prediction
Multi-Objective Hyperparameter Optimization—An Overview
Director: Deep Hierarchical Planning from Pixels
Boosting Search Engines with Interactive Agents
Towards Learning Universal Hyperparameter Optimizers with Transformers
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments
Effective Mutation Rate Adaptation through Group Elite Selection
Semantic Exploration from Language Abstractions and Pretrained Representations
Habitat-Web: Learning Embodied Object-Search Strategies from Human Demonstrations at Scale
CLIP on Wheels (CoW): Zero-Shot Object Navigation as Object Localization and Exploration
Policy improvement by planning with Gumbel
Evolving Curricula with Regret-Based Environment Design
VAPO: Affordance Learning from Play for Sample-Efficient Policy Learning
Learning Causal Overhypotheses through Exploration in Children and Computational Models
Policy Learning and Evaluation with Randomized Quasi-Monte Carlo
NeuPL: Neural Population Learning
ODT: Online Decision Transformer
EvoJAX: Hardware-Accelerated Neuroevolution
LID: Pre-Trained Language Models for Interactive Decision-Making
Accelerated Quality-Diversity for Robotics through Massive Parallelism
Rotting Infinitely Many-armed Bandits
Don’t Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning (ExORL)
Any-Play: An Intrinsic Augmentation for Zero-Shot Coordination
Evolution Gym: A Large-Scale Benchmark for Evolving Soft Robots
Environment Generation for Zero-Shot Compositional Reinforcement Learning
Safe Deep RL in 3D Environments using Human Feedback
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
Maximum Entropy Population Based Training for Zero-Shot Human-AI Coordination
The costs and benefits of dispersal in small populations
The geometry of decision-making in individuals and collectives
An Experimental Design Perspective on Model-Based Reinforcement Learning
JueWu-MC: Playing Minecraft with Sample-efficient Hierarchical Reinforcement Learning
Procedural Generalization by Planning with Self-Supervised World Models
Correspondence between neuroevolution and gradient descent
URLB: Unsupervised Reinforcement Learning Benchmark
Mastering Atari Games with Limited Data
Discovering and Achieving Goals via World Models
The structure of genotype-phenotype maps makes fitness landscapes navigable
Replay-Guided Adversarial Environment Design
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning
Monkey Plays Pac-Man with Compositional Strategies and Hierarchical Decision-making
Neural autopilot and context-sensitivity of habits
Algorithmic Balancing of Familiarity, Similarity, & Discovery in Music Recommendations
TrufLL: Learning Natural Language Generation from Scratch
Is Curiosity All You Need? On the Utility of Emergent Behaviors from Curious Exploration
Bootstrapped Meta-Learning
Open-Ended Learning Leads to Generally Capable Agents
Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability
Imitation-driven Cultural Collapse
Multi-task curriculum learning in a complex, visual, hard-exploration domain: Minecraft
Learning to hesitate
Planning for Novelty: Width-Based Algorithms for Common Problems in Control, Planning and Reinforcement Learning
Trajectory Transformer: Reinforcement Learning as One Big Sequence Modeling Problem
From Motor Control to Team Play in Simulated Humanoid Football
Reward is enough
Principled Exploration via Optimistic Bootstrapping and Backward Induction
Intelligence and Unambitiousness Using Algorithmic Information Theory
Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks
On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning
What Are Bayesian Neural Network Posteriors Really Like?
Epistemic Autonomy: Self-supervised Learning in the Mammalian Hippocampus
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020
Flexible modulation of sequence generation in the entorhinal-hippocampal system
Reinforcement Learning, Bit by Bit
Asymmetric self-play for automatic goal discovery in robotic manipulation
Informational Herding, Optimal Experimentation, and Contrarianism
Go-Explore: First return, then explore
TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning
Proof Artifact Co-training for Theorem Proving with Language Models
The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors
Curriculum Learning: A Survey
MAP-Elites Enables Powerful Stepping Stones and Diversity for Modular Robotics
Is Pessimism Provably Efficient for Offline RL?
Monte-Carlo Graph Search for AlphaZero
Imitating Interactive Intelligence
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian
Meta-trained agents implement Bayes-optimal agents
Learning not to learn: Nature versus nurture in silico
The Child as Hacker
Assessing Game Balance with AlphaZero: Exploring Alternative Rule Sets in Chess
The Temporal Dynamics of Opportunity Costs: A Normative Account of Cognitive Fatigue and Boredom
The Overfitted Brain: Dreams evolved to assist generalization
The NetHack Learning Environment
Exploration Strategies in Deep Reinforcement Learning
Synthetic Petri Dish: A Novel Surrogate Model for Rapid Architecture Search
Automatic Discovery of Interpretable Planning Strategies
IJON: Exploring Deep State Spaces via Fuzzing
Planning to Explore via Self-Supervised World Models
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Pitfalls of learning a reward function online
First return, then explore
Real World Games Look Like Spinning Tops
Approximate exploitability: Learning a best response in large games
Agent57: Outperforming the human Atari benchmark
Agent57: Outperforming the Atari Human Benchmark
Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions
Meta-learning curiosity algorithms
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Never Give Up: Learning Directed Exploration Strategies
Effective Diversity in Population Based Reinforcement Learning
Near-perfect point-goal navigation from 2.5 billion frames of experience
microbatchGAN: Stimulating Diversity with Multi-Adversarial Discrimination
Learning Human Objectives by Evaluating Hypothetical Behavior
Optimal Policies Tend to Seek Power
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames
Emergent Tool Use From Multi-Agent Autocurricula
Emergent Tool Use from Multi-Agent Interaction § Surprising behavior
R2D3: Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment
An Optimistic Perspective on Offline Reinforcement Learning
Meta Reinforcement Learning
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning
ICML 2019 Notes
Human-level performance in 3D multiplayer games with population-based reinforcement learning
AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence
Learning to Reason in Large Theories without Imitation
Reinforcement Learning, Fast and Slow
Meta reinforcement learning as task inference
Meta-learning of Sequential Strategies
The MineRL 2019 Competition on Sample Efficient Reinforcement Learning using Human Priors
π-IW: Deep Policies for Width-Based Planning in Pixel Domains
Learning To Follow Directions in Street View
A Generalized Framework for Population Based Training
Go-Explore: a New Approach for Hard-Exploration Problems
Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their Solutions
Is the FDA too conservative or too aggressive?: A Bayesian decision analysis of clinical trial design
V-Fuzz: Vulnerability-Oriented Evolutionary Fuzzing
Common neural code for reward and information value
Machine-Learning-Guided Directed Evolution for Protein Engineering
Enjoy it again: Repeat experiences are less repetitive than people think
Evolutionary-Neural Hybrid Agents for Architecture Search
The Bayesian Superorganism III: externalized memories facilitate distributed sampling
Exploration in the wild
Off-Policy Deep Reinforcement Learning without Exploration
An Introduction to Deep Reinforcement Learning
The Bayesian Superorganism I: collective probability estimation
Exploration by Random Network Distillation
Computational noise in reward-guided learning drives behavioral variability in volatile environments
RND: Large-Scale Study of Curiosity-Driven Learning
Visual Reinforcement Learning with Imagined Goals
Is Q-learning Provably Efficient?
Improving width-based planning with compact policies
Construction of arbitrarily strong amplifiers of natural selection using evolutionary graph theory
Re-evaluating Evaluation
DVRL: Deep Variational Reinforcement Learning for POMDPs
Mix&Match—Agent Curricula for Reinforcement Learning
Playing hard exploration games by watching YouTube
Observe and Look Further: Achieving Consistent Performance on Atari
Generalization and search in risky environments
Toward Diverse Text Generation with Inverse Reinforcement Learning
Efficient Multi-objective Neural Architecture Search via Lamarckian Evolution
Learning to Navigate in Cities Without a Map
The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities
Some Considerations on Learning to Explore via Meta-Reinforcement Learning
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration
Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari
One Big Net For Everything
Learning to Search with MCTSnets
Learning and Querying Fast Generative Models for Reinforcement Learning
Safe Exploration in Continuous Action Spaces
Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning
Deep Reinforcement Fuzzing
Planning Chemical Syntheses With Deep Neural Networks and Symbolic AI
Generalization Guides Human Exploration in Vast Decision Spaces
Innovation and cumulative culture through tweaks and leaps in online programming contests
A Flexible Approach to Automated RNN Architecture Generation
Finding Competitive Network Architectures Within a Day Using UCT
Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
The paradoxical sustainability of periodic migration and habitat destruction
Posterior Sampling for Large Scale Reinforcement Learning
Policy Optimization by Genetic Distillation
Emergent Complexity via Multi-Agent Competition
An Analysis of the Value of Information when Exploring Stochastic, Discrete Multi-Armed Bandits
The Uncertainty Bellman Equation and Exploration
Changing Their Tune: How Consumers’ Adoption of Online Streaming Affects Music Consumption and Discovery
A Rational Choice Framework for Collective Behavior
Imagination-Augmented Agents for Deep Reinforcement Learning
Distral: Robust Multitask Reinforcement Learning
The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously
Emergence of Locomotion behaviors in Rich Environments
Noisy Networks for Exploration
CAN: Creative Adversarial Networks, Generating "Art" by Learning About Styles and Deviating from Style Norms
Device Placement Optimization with Reinforcement Learning
Towards Synthesizing Complex Programs from Input-Output Examples
Scalable Generalized Linear Bandits: Online Computation and Hashing
DeepXplore: Automated Whitebox Testing of Deep Learning Systems
Recurrent Environment Simulators
Learned Optimizers that Scale and Generalize
Evolution Strategies as a Scalable Alternative to Reinforcement Learning
Large-Scale Evolution of Image Classifiers
CoDeepNEAT: Evolving Deep Neural Networks
Rotting Bandits
Neural Combinatorial Optimization with Reinforcement Learning
Neural Data Filter for Bootstrapping Stochastic Gradient Descent
Search in Patchy Media: Exploitation-Exploration Tradeoff
Towards Information-Seeking Agents
Exploration and exploitation of Victorian science in Darwin’s reading notebooks
Learning to Learn without Gradient Descent by Gradient Descent
Learning to Perform Physics Experiments via Deep Reinforcement Learning
Neural Architecture Search with Reinforcement Learning
Combating Reinforcement Learning’s Sisyphean Curse with Intrinsic Fear
Bayesian Reinforcement Learning: A Survey
Human collective intelligence as distributed Bayesian inference
Universal Darwinism as a process of Bayesian inference
Unifying Count-Based Exploration and Intrinsic Motivation
D-TS: Double Thompson Sampling for Dueling Bandits
Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning
Deep Exploration via Bootstrapped DQN
The Netflix Recommender System
On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models
Online Batch Selection for Faster Training of Neural Networks
MAP-Elites: Illuminating search spaces by mapping elites
What My Deep Model Doesn't Know...
The Psychology and Neuroscience of Curiosity
Thompson sampling with the online bootstrap
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models
Robots that can adapt like animals
Freeze-Thaw Bayesian Optimization
Search for the Wreckage of Air France Flight AF 447
(More) Efficient Reinforcement Learning via Posterior Sampling
Model-Based Bayesian Exploration
PUCT: Continuous Upper Confidence Trees with Polynomial Exploration-Consistency
(More) Efficient Reinforcement Learning via Posterior Sampling [PSRL]
629d1cdd4ed81ada32f4b9638501d15d3d891556.pdf#deepmind
Experimental design for Partially Observed Markov Decision Processes
Learning is planning: near Bayes-optimal reinforcement learning via Monte-Carlo tree search
PILCO: A Model-Based and Data-Efficient Approach to Policy Search
Abandoning Objectives: Evolution Through the Search for Novelty Alone
Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments
Age-fitness pareto optimization
Monte-Carlo Planning in Large POMDPs
Formal Theory of Creativity & Fun & Intrinsic Motivation (1990–2010)
The Epistemic Benefit of Transient Diversity
Specialization Effect and Its Influence on Memory and Problem Solving in Expert Chess Players
Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes
Pure Exploration for Multi-Armed Bandit Problems
Exploiting Open-Endedness to Solve Problems Through the Search for Novelty
Towards Efficient Evolutionary Design of Autonomous Robots
Resilient Machines Through Continuous Self-Modeling
ALPS: the age-layered population structure for reducing the problem of premature convergence
Bayesian Adaptive Exploration
NEAT: Evolving Neural Networks through Augmenting Topologies
A Bayesian Framework for Reinforcement Learning
Case studies in evolutionary experimentation and computation
Efficient Progressive Sampling
Evolving 3D Morphology and Behavior by Competition
b5f0d7b48d78560834dc391504a8c36149d6e802.pdf
Interactions between Learning and Evolution
Evolution Strategy: Nature’s Way of Optimization
The Analysis of Sequential Experiments with Feedback to Subjects
Evolutionsstrategien
Evolutionsstrategie: Optimierung technischer Systeme nach Prinzipien der biologischen Evolution
The Usefulness of Useless Knowledge
Curiosity Killed the Mario
Brian Christian on Computer Science Algorithms That Tackle Fundamental and Universal Problems
e38fdd2e3d19fef222bb1222fbe63da6a0fe9ea6.html
Solving Zelda With the Antithesis SDK
974bd67fde19017d4a9c5879b69275021e18cdd5.html
Goodhart’s Law, Diversity and a Series of Seemingly Unrelated Toy Problems
4ed8cac77930aa2bfd9d9d87fc0c6320d627666f.html
Why Generalization in RL Is Difficult: Epistemic POMDPs and Implicit Partial Observability [Blog]
Bayesian Optimization Book
Temporal Difference Learning and TD-Gammon
An Experimental Design Perspective on Model-Based Reinforcement Learning [Blog]
f081a958085e5690489c18884fa913a7190d0688.html
Safety-First AI for Autonomous Data Center Cooling and Industrial Control
Pulling JPEGs out of Thin Air
d7117e8daef1d2b88752309178476d7d627b8908.html
Curriculum For Reinforcement Learning
82f88b3c03ad0b252a33823c09b770832a95bbcc.html#openai
Why Testing Self-Driving Cars in SF Is Challenging but Necessary
Reinforcement Learning With Prediction-Based Rewards
Prompting Diverse Ideas: Increasing AI Idea Variance
You Need a Novelty Budget
ChatGPT As Muse, Not Oracle
Conditions for Mathematical Equivalence of Stochastic Gradient Descent and Natural Selection
Probable Points and Credible Intervals, Part 2: Decision Theory
AI Is Learning How to Create Itself
2874fc1c58ced20eb47a85ca46af67972fcf2ab4.html
Montezuma's Revenge Solved by Go-Explore, a New Algorithm for Hard-Exploration Problems (Sets Records on Pitfall, Too)
Monkeys Play Pac-Man
Playing Montezuma's Revenge With Intrinsic Motivation
design#future-tag-features

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http://bayesiandeeplearning.org/2017/papers/57.pdf
9542903facdeee8a78641311471be0bc6fb2a482.pdf
http://incompleteideas.net/book/ebook/node45.html
528eb890c177e0a5d26694aea7131d449ca9022e.html
http://vision.psych.umn.edu/groups/schraterlab/dearden98bayesian.pdf
https://deepmind.google/discover/blog/capture-the-flag-the-emergence-of-complex-cooperative-agents/-the-emergence-of-complex-cooperative-agents
https://engineeringideas.substack.com/p/review-of-why-greatness-cannot-be
https://jsomers.net/e-coli-chemotaxis/
https://nathanieltravis.com/2022/01/17/is-human-behavior-just-elaborate-running-and-tumbling/
https://onlinelibrary.wiley.com/doi/full/10.1002/bdm.2360
https://openai.com/blog/learning-montezumas-revenge-from-a-single-demonstration/
https://openai.com/research/vpt
https://patentimages.storage.googleapis.com/57/53/22/91b8a6792dbb1e/US20180204116A1.pdf#deepmind
https://people.idsia.ch/~juergen/FKI-126-90_(revised)bw_ocr.pdf
666a90978bf0db98cb2afd8edf854870779a6f0c.pdf
https://storage.googleapis.com/pub-tools-public-publication-data/pdf/f52ac33bc9d1adecd3a8037a7009b185fd934f0e.pdf
75839823347df79e49d65c3912f17f35e466a648.pdf
https://tor-lattimore.com/downloads/book/book.pdf#page=412
762d4ee657af5f8ac4c3f5096fac3c5ba87c71f0.pdf#page=412
https://www.freaktakes.com/p/the-past-and-present-of-computer
https://www.microsoft.com/en-us/research/blog/phi-2-the-surprising-power-of-small-language-models/
https://www.nature.com/articles/s41467-020-19244-4#deepmind
https://www.nature.com/articles/s41534-019-0241-0
https://www.quantamagazine.org/clever-machines-learn-how-to-be-curious-20170919/
f68e4e5dc1dd15828679d7cabe5b568097d1264e.html
https://www.quantamagazine.org/random-search-wired-into-animals-may-help-them-hunt-20200611/
4ba297594338ba879254f1e055fd62c491eca45f.html
https://www.reddit.com/r/MachineLearning/comments/a0nnp7/r_montezumas_revenge_solved_by_goexplore_a_new/
df2f27d90614f7333aae0b60f9acbe4e34cfa8cd.html
https://www.youtube.com/watch?v=DcYLT37ImBY
https://x.com/Aella_Girl/status/1594144435000213505
https://x.com/Omorfiamorphism/status/1564633854119477257
https://x.com/kenneth0stanley/status/1733571230803058920
https://x.com/pirroh/status/1694516986561307022
Intelligent Go-Explore (IGE): Standing on the Shoulders of Giant Foundation Models
Jeff Clune—Professor—Computer Science—University of British Columbia
https%253A%252F%252Farxiv.org%252Fabs%252F2405.15143.html
Small batch deep reinforcement learning
https%253A%252F%252Farxiv.org%252Fabs%252F2310.03882%2523deepmind.html
Diversifying AI: Towards Creative Chess with AlphaZero (AZ_db)
https%253A%252F%252Farxiv.org%252Fabs%252F2308.09175%2523deepmind.html
Supervised Pretraining Can Learn In-Context Reinforcement Learning
https%253A%252F%252Farxiv.org%252Fabs%252F2306.14892.html
You And Your Research
%252Fdoc%252Fscience%252F1986-hamming.html
MarioGPT: Open-Ended Text2Level Generation through Large Language Models
https%253A%252F%252Farxiv.org%252Fabs%252F2302.05981.html
DreamerV3: Mastering Diverse Domains through World Models
https%253A%252F%252Farxiv.org%252Fabs%252F2301.04104%2523deepmind.html
Vote-K: Selective Annotation Makes Language Models Better Few-Shot Learners
Luke Zettlemoyer
https%253A%252F%252Farxiv.org%252Fabs%252F2209.01975.html
Trajectory Autoencoding Planner: Efficient Planning in a Compact Latent Action Space
https%253A%252F%252Farxiv.org%252Fabs%252F2208.10291.html
Value-free random exploration is linked to impulsivity
https%253A%252F%252Fwww.nature.com%252Farticles%252Fs41467-022-31918-9.html
Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos
Jeff Clune—Professor—Computer Science—University of British Columbia
https%253A%252F%252Farxiv.org%252Fabs%252F2206.11795%2523openai.html
Director: Deep Hierarchical Planning from Pixels
https%253A%252F%252Farxiv.org%252Fabs%252F2206.04114%2523google.html
Boosting Search Engines with Interactive Agents
https%253A%252F%252Fopenreview.net%252Fforum%253Fid%253D0ZbPmmB61g%2523google.html
Towards Learning Universal Hyperparameter Optimizers with Transformers
https%253A%252F%252Farxiv.org%252Fabs%252F2205.13320%2523google.html
Semantic Exploration from Language Abstractions and Pretrained Representations
Language Understanding Grounded in Perception and Action
https%253A%252F%252Farxiv.org%252Fabs%252F2204.05080%2523deepmind.html
Habitat-Web: Learning Embodied Object-Search Strategies from Human Demonstrations at Scale
https%253A%252F%252Farxiv.org%252Fabs%252F2204.03514%2523facebook.html
Policy improvement by planning with Gumbel
Julian Schrittwieser
https%253A%252F%252Fopenreview.net%252Fforum%253Fid%253DbERaNdoegnO%2523deepmind.html
NeuPL: Neural Population Learning
Nicolas Heess
https%253A%252F%252Farxiv.org%252Fabs%252F2202.07415%2523deepmind.html
EvoJAX: Hardware-Accelerated Neuroevolution
https%253A%252F%252Farxiv.org%252Fabs%252F2202.05008%2523google.html
Maximum Entropy Population Based Training for Zero-Shot Human-AI Coordination
https%253A%252F%252Farxiv.org%252Fabs%252F2112.11701%2523tencent.html
Procedural Generalization by Planning with Self-Supervised World Models
Julian Schrittwieser
Sherjil Ozair
https%253A%252F%252Farxiv.org%252Fabs%252F2111.01587%2523deepmind.html
Mastering Atari Games with Limited Data
https%253A%252F%252Farxiv.org%252Fabs%252F2111.00210.html
Algorithmic Balancing of Familiarity, Similarity, & Discovery in Music Recommendations
%252Fdoc%252Freinforcement-learning%252Fexploration%252F2021-mehrotra.pdf%2523spotify.html
Trajectory Transformer: Reinforcement Learning as One Big Sequence Modeling Problem
Sergey Levine
https%253A%252F%252Ftrajectory-transformer.github.io%252F.html
From Motor Control to Team Play in Simulated Humanoid Football
Guy Lever
Nicolas Heess
https%253A%252F%252Farxiv.org%252Fabs%252F2105.12196%2523deepmind.html
Reward is enough
https%253A%252F%252Fwww.sciencedirect.com%252Fscience%252Farticle%252Fpii%252FS0004370221000862%2523deepmind.html
Go-Explore: First return, then explore
Jeff Clune—Professor—Computer Science—University of British Columbia
%252Fdoc%252Freinforcement-learning%252Fexploration%252F2021-ecoffet.pdf%2523uber.html
The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors
John Schulman’s Homepage
https%253A%252F%252Farxiv.org%252Fabs%252F2101.11071.html
Imitating Interactive Intelligence
Language Understanding Grounded in Perception and Action
https%253A%252F%252Farxiv.org%252Fabs%252F2012.05672%2523deepmind.html
Assessing Game Balance with AlphaZero: Exploring Alternative Rule Sets in Chess
https%253A%252F%252Farxiv.org%252Fabs%252F2009.04374%2523deepmind.html
Agent57: Outperforming the human Atari benchmark
https%253A%252F%252Fdeepmind.google%252Fdiscover%252Fblog%252Fagent57-outperforming-the-human-atari-benchmark%252F.html
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames
https%253A%252F%252Farxiv.org%252Fabs%252F1911.00357%2523facebook.html
Emergent Tool Use from Multi-Agent Interaction § Surprising behavior
https://x.com/bobmcgrewai
Igor Mordatch
https%253A%252F%252Fopenai.com%252Fresearch%252Femergent-tool-use%2523surprisingbehaviors.html
ICML 2019 Notes
https%253A%252F%252Fdavid-abel.github.io%252Fnotes%252Ficml_2019.pdf.html
Human-level performance in 3D multiplayer games with population-based reinforcement learning
Guy Lever
Koray Kavukcuoglu
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Improving width-based planning with compact policies
https%253A%252F%252Farxiv.org%252Fabs%252F1806.05898.html
Construction of arbitrarily strong amplifiers of natural selection using evolutionary graph theory
https%253A%252F%252Fwww.nature.com%252Farticles%252Fs42003-018-0078-7.html
Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari
Ilya Loshchilov
Profile – Machine Learning Lab
https%253A%252F%252Farxiv.org%252Fabs%252F1802.08842.html
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
Jeff Clune—Professor—Computer Science—University of British Columbia
https%253A%252F%252Farxiv.org%252Fabs%252F1712.06567%2523uber.html
The Netflix Recommender System
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Age-fitness pareto optimization
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Monte-Carlo Planning in Large POMDPs
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Specialization Effect and Its Influence on Memory and Problem Solving in Expert Chess Players
https%253A%252F%252Fonlinelibrary.wiley.com%252Fdoi%252F10.1111%252Fj.1551-6709.2009.01030.x.html
ALPS: the age-layered population structure for reducing the problem of premature convergence
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Wikipedia Bibliography: