deep reinforcement learning

DataFunSummit

Aug 5, 2023 · Operations

Intelligent Decision-Making in Supply Chains: Conference Overview and Speaker Sessions

The forum gathers leading industry experts and scholars to discuss intelligent decision technologies across manufacturing, retail, energy, and pharmaceutical supply chains, presenting case studies, deep reinforcement learning applications, and optimization methods that drive agile, data‑driven supply chain transformation.

Artificial Intelligencedecision optimizationdeep reinforcement learning

0 likes · 9 min read

Intelligent Decision-Making in Supply Chains: Conference Overview and Speaker Sessions

DataFunTalk

Apr 17, 2023 · Artificial Intelligence

Speculation: GPT-5 May Adopt Model‑Based Deep Reinforcement Learning for Unlimited Self‑Improvement

The article argues that the next generation GPT is likely to employ model‑based deep reinforcement learning, turning the model into both a policy and a world model, which could enable rapid, data‑efficient self‑enhancement but also raise serious safety and societal risks.

AI safetyGPT-5deep reinforcement learning

0 likes · 4 min read

Speculation: GPT-5 May Adopt Model‑Based Deep Reinforcement Learning for Unlimited Self‑Improvement

DaTaobao Tech

Aug 18, 2022 · Artificial Intelligence

Introduction to Deep Reinforcement Learning: Theory, Algorithms, and Applications

This article introduces deep reinforcement learning by explaining its Markov decision process foundations, then categorizes the main algorithm families—value‑based methods like DQN, policy‑based approaches such as PG/DPG/DDPG, and actor‑critic techniques including A3C, PPO, and DDPG—detailing their architectures, training procedures, and key advantages.

DQNMDPactor-critic

0 likes · 14 min read

Introduction to Deep Reinforcement Learning: Theory, Algorithms, and Applications

Tencent Cloud Developer

Apr 8, 2022 · Databases

Tencent Cloud Native Database AI Autonomy: SIGMOD Research and Intelligent Tuning System

Tencent Cloud’s native database team achieved a SIGMOD breakthrough by embedding AI into MySQL, creating an autonomous “database brain” that uses deep‑reinforcement learning, genetic pre‑heating and a closed‑loop learner/actor architecture to automatically observe, analyze, and tune diverse workloads, delivering rapid performance gains, anomaly detection, and self‑optimizing features while addressing adaptability, stability, and interpretability challenges.

AI optimizationCDBTuneDatabase Autonomy

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Tencent Cloud Native Database AI Autonomy: SIGMOD Research and Intelligent Tuning System

Tencent Tech

Dec 31, 2020 · Artificial Intelligence

How Tencent’s WeKick AI Dominated the Google Football Kaggle Competition

Tencent AI Lab’s WeKick AI clinched the inaugural Google Football Kaggle championship with a score of 1785.8, outpacing over 1,100 research teams by leveraging a migrated full‑stack architecture, custom reinforcement‑learning frameworks, GAIL imitation learning, and a multi‑style League training pipeline that together showcase the power and generality of deep reinforcement learning for complex multi‑agent tasks.

AIGAILGoogle Football

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How Tencent’s WeKick AI Dominated the Google Football Kaggle Competition

Tencent Database Technology

Jul 8, 2019 · Databases

SIGMOD 2019 Highlights: Blockchain Keynote, CDBTune Paper on Cloud Database Tuning, and Emerging Database Research

The report summarizes SIGMOD/PODS 2019 in Amsterdam, covering a blockchain-focused keynote, the CDBTune paper on end‑to‑end automatic cloud database tuning using deep reinforcement learning, modern hardware research, award‑winning systems, and related industry activities, providing a comprehensive academic overview.

BlockchainCloud DatabaseDatabase Tuning

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SIGMOD 2019 Highlights: Blockchain Keynote, CDBTune Paper on Cloud Database Tuning, and Emerging Database Research

Dada Group Technology

Jun 9, 2017 · Artificial Intelligence

Deep Reinforcement Learning: Concepts, Black‑Box Optimization, and the Cross‑Entropy Method

This article introduces reinforcement learning and deep reinforcement learning, explains key algorithms such as DQN and policy gradients, discusses black‑box optimization and the cross‑entropy method, and provides resources and code examples for further study.

Artificial IntelligenceDQNblack-box optimization

0 likes · 7 min read

Deep Reinforcement Learning: Concepts, Black‑Box Optimization, and the Cross‑Entropy Method