Cover Image

Learning and Improving Backgammon Strategy

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Galperin, Gregory R.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Neural and Evolutionary Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On-line Policy Improvement using Monte-Carlo Search
by: Tesauro, Gerald, et al.
Published: (2025)

Learning Heuristics for Transit Network Design and Improvement with Deep Reinforcement Learning
by: Holliday, Andrew, et al.
Published: (2024)

Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning
by: Qiu, Xin, et al.
Published: (2025)

CDRL: A Reinforcement Learning Framework Inspired by Cerebellar Circuits and Dendritic Computational Strategies
by: Zhang, Sibo, et al.
Published: (2026)

Unveiling the Potential of Spiking Dynamics in Graph Representation Learning through Spatial-Temporal Normalization and Coding Strategies
by: Xu, Mingkun, et al.
Published: (2024)

Stein Variational Evolution Strategies
by: Braun, Cornelius V., et al.
Published: (2024)

Large Language Models As Evolution Strategies
by: Lange, Robert Tjarko, et al.
Published: (2024)

Heuristically Adaptive Diffusion-Model Evolutionary Strategy
by: Hartl, Benedikt, et al.
Published: (2024)

An Improved Grey Wolf Optimization Algorithm for Heart Disease Prediction
by: Niu, Sihan, et al.
Published: (2024)

Bridging Models to Defend: A Population-Based Strategy for Robust Adversarial Defense
by: Wang, Ren, et al.
Published: (2023)

Gradient-Free Training of Spiking Neural Networks via Low-Rank Evolution Strategies
by: Patankar, Dhruv, et al.
Published: (2026)

Improving equilibrium propagation without weight symmetry through Jacobian homeostasis
by: Laborieux, Axel, et al.
Published: (2023)

Improved Forecasting Using a PSO-RDV Framework to Enhance Artificial Neural Network
by: Aribe Jr, Sales
Published: (2024)

QSLM: A Performance- and Memory-aware Quantization Framework with Tiered Search Strategy for Spike-driven Language Models
by: Putra, Rachmad Vidya Wicaksana, et al.
Published: (2026)

Self-Improving Language Models for Evolutionary Program Synthesis: A Case Study on ARC-AGI
by: Pourcel, Julien, et al.
Published: (2025)

Statistical Properties of the King Wen Sequence: An Anti-Habituation Structure That Does Not Improve Neural Network Training
by: Chan, Augustin
Published: (2026)

An Efficient Reconstructed Differential Evolution Variant by Some of the Current State-of-the-art Strategies for Solving Single Objective Bound Constrained Problems
by: Tao, Sichen, et al.
Published: (2024)

The Alpha-Alternator: Dynamic Adaptation To Varying Noise Levels In Sequences Using The Vendi Score For Improved Robustness and Performance
by: Rezaei, Mohammad Reza, et al.
Published: (2025)

SpiKernel: A Kernel Size Exploration Methodology for Improving Accuracy of the Embedded Spiking Neural Network Systems
by: Putra, Rachmad Vidya Wicaksana, et al.
Published: (2024)

General-Purpose In-Context Learning by Meta-Learning Transformers
by: Kirsch, Louis, et al.
Published: (2022)

Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks
by: Xiao, Mingqing, et al.
Published: (2024)

Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning
by: Kao, Chia-Hsiang, et al.
Published: (2024)

Dynamic Reinforcement Learning for Actors
by: Shibata, Katsunari
Published: (2025)

Causal Learning with Neural Assemblies
by: Kopadi, Evangelia, et al.
Published: (2026)

On the Temperature of Machine Learning Systems
by: Zhang, Dong
Published: (2024)

Neuron-centric Hebbian Learning
by: Ferigo, Andrea, et al.
Published: (2024)

Learning Graph Quantized Tokenizers
by: Wang, Limei, et al.
Published: (2024)

Towards White Box Deep Learning
by: Satkiewicz, Maciej
Published: (2024)

Fitness Approximation through Machine Learning
by: Tzruia, Itai, et al.
Published: (2023)

Evolving Reservoirs for Meta Reinforcement Learning
by: Léger, Corentin, et al.
Published: (2023)

Prospective Compression in Human Abstraction Learning
by: Cano, Leonardo Hernandez, et al.
Published: (2026)

Automated Deep Learning for Load Forecasting
by: Keisler, Julie, et al.
Published: (2024)

Introduction to Predictive Coding Networks for Machine Learning
by: Stenlund, Mikko
Published: (2025)

Half-Space Feature Learning in Neural Networks
by: Yadav, Mahesh Lorik, et al.
Published: (2024)

Deep Reinforcement Learning with Spiking Q-learning
by: Chen, Ding, et al.
Published: (2022)

Mechanistic Neural Networks for Scientific Machine Learning
by: Pervez, Adeel, et al.
Published: (2024)

Offline Model-Based Optimization by Learning to Rank
by: Tan, Rong-Xi, et al.
Published: (2024)

Understanding Deep Learning via Notions of Rank
by: Razin, Noam
Published: (2024)

On Non-Linear operators for Geometric Deep Learning
by: Sergeant-Perthuis, Grégoire, et al.
Published: (2022)

QF-tuner: Breaking Tradition in Reinforcement Learning
by: Jumaah, Mahmood A., et al.
Published: (2024)