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reinforcement learning

822 articles · Page 9 of 9
JD Tech
JD Tech
Sep 12, 2018 · Artificial Intelligence

JD Autonomous Delivery Robots: Technologies, Patents, and Future Challenges

The article details JD's third‑generation autonomous delivery robots, covering their multi‑sensor fusion localization, deep‑learning perception, reinforcement‑learning motion control, extensive patent portfolio, and upcoming technical hurdles such as high‑precision mapping and lidar cost, while also inviting public voting for patent awards.

AI navigationJD Logisticsautonomous robots
0 likes · 8 min read
JD Autonomous Delivery Robots: Technologies, Patents, and Future Challenges
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 13, 2018 · Artificial Intelligence

How We Won OpenAI’s Retro Contest: Joint PPO Mastery on Sonic Games

This article analyzes OpenAI’s Retro Contest on Sonic the Hedgehog, explains why reinforcement learning generalization is crucial for AGI, and details the winning team’s joint PPO pipeline, engineering optimizations, training strategies, and final performance compared to human baselines.

OpenAI Retro ContestRL generalizationSonic game
0 likes · 21 min read
How We Won OpenAI’s Retro Contest: Joint PPO Mastery on Sonic Games
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 23, 2018 · Fundamentals

Top Technical Books Recommended by Alibaba Experts for World Book Day

On World Book Day, nine Alibaba technology veterans share a curated list of essential technical books—covering software testing, design patterns, AI, machine learning, reinforcement learning, Rust, and database architecture—offering concise reasons why each title is valuable for developers and engineers.

Database ArchitectureDesign PatternsRust programming
0 likes · 10 min read
Top Technical Books Recommended by Alibaba Experts for World Book Day
Tencent Cloud Developer
Tencent Cloud Developer
Mar 15, 2018 · Artificial Intelligence

Learning Long-Horizon Surgical Robot Tasks via Transition State Clustering, SWIRL, and DDCO

The article surveys three recent approaches—Transition State Clustering, Sequential Windowed Inverse Reinforcement Learning, and Deep Discovery of Continuous Options—that automatically segment long‑horizon surgical‑robot demonstrations into sub‑tasks, learn hierarchical policies from limited data, and achieve markedly higher success rates on da Vinci cutting, tension, and needle‑picking tasks.

hierarchical learningimitation learningreinforcement learning
0 likes · 18 min read
Learning Long-Horizon Surgical Robot Tasks via Transition State Clustering, SWIRL, and DDCO
Alibaba Cloud Developer
Alibaba Cloud Developer
Feb 5, 2018 · Artificial Intelligence

How Alibaba’s AliMe Evolved in 2017: AI Architecture, Algorithms, and Real‑World Impact

In 2017 Alibaba's AliMe chatbot platform expanded from a single‑company solution to a multilingual, multi‑channel AI service, introducing platform‑level SaaS/PaaS capabilities, a seven‑layer front‑end architecture, modular back‑end design, advanced intent recognition, knowledge‑graph‑driven product management, reinforcement‑learning‑based recommendation, and machine‑reading comprehension for enterprise and consumer use cases.

AI platformAlibabaChatbot
0 likes · 23 min read
How Alibaba’s AliMe Evolved in 2017: AI Architecture, Algorithms, and Real‑World Impact
Hulu Beijing
Hulu Beijing
Dec 6, 2017 · Artificial Intelligence

How Deep Reinforcement Learning Powers Video Game AI: From Q‑Learning to Atari Mastery

This article explains how deep reinforcement learning, built upon traditional Q‑learning and enhanced with techniques like experience replay, enables agents to play Atari video games directly from raw pixel inputs, illustrating the key differences, processing steps, and the significance of this breakthrough in AI.

AtariQ-Learningdeep Q‑learning
0 likes · 5 min read
How Deep Reinforcement Learning Powers Video Game AI: From Q‑Learning to Atari Mastery
Hulu Beijing
Hulu Beijing
Dec 5, 2017 · Artificial Intelligence

What Is Reinforcement Learning? Core Concepts Explained

This article introduces the fundamental concepts of reinforcement learning, describing its origins, key components such as agents, environments, states, actions, and rewards, explaining the Markov decision process framework, and highlighting common algorithms like Q‑learning, policy gradients, and actor‑critic methods.

AIAlgorithmsMDP
0 likes · 4 min read
What Is Reinforcement Learning? Core Concepts Explained
Ctrip Technology
Ctrip Technology
Oct 19, 2017 · Artificial Intelligence

Intelligent Human‑Computer Interaction: Technical Practices of Alibaba’s “Ali Xiaomi” Chatbot

This article presents a comprehensive overview of Alibaba’s intelligent chatbot “Ali Xiaomi”, covering industry context, e‑commerce deployment, NLU architecture, intent‑matching layers, deep‑learning‑based intent classification, reinforcement‑learning‑driven recommendation, knowledge‑graph‑enhanced services, and hybrid retrieval‑generation dialogue models, with future outlooks for AI‑driven interaction.

Knowledge GraphNatural Language Understandingdeep learning
0 likes · 18 min read
Intelligent Human‑Computer Interaction: Technical Practices of Alibaba’s “Ali Xiaomi” Chatbot
ITPUB
ITPUB
Sep 14, 2017 · Artificial Intelligence

How Salesforce’s Seq2SQL Turns Natural Language into SQL with Reinforcement Learning

Salesforce’s recent research introduces Seq2SQL, a reinforcement‑learning‑driven sequence‑to‑sequence model that translates natural‑language questions into SQL queries, eliminating the need to learn SQL, and includes the large WikiSQL dataset built from crowdsourced NL‑SQL pairs for training and evaluation.

AISQL GenerationSeq2SQL
0 likes · 6 min read
How Salesforce’s Seq2SQL Turns Natural Language into SQL with Reinforcement Learning
AntTech
AntTech
Aug 4, 2017 · Artificial Intelligence

Key Insights from Ant Financial VP Dr. Qi Yuan’s Talk on the Development and Application of Financial Intelligence at CCAI 2017

The article summarizes Dr. Qi Yuan’s presentation at CCAI 2017, detailing Ant Financial’s AI‑driven solutions for financial services—including risk control, intelligent assistants, large‑scale machine learning, reinforcement‑learning marketing, a model‑service platform, and a computer‑vision damage‑assessment system—while highlighting technical challenges, platform architecture, and the company’s open‑tech philosophy.

Artificial IntelligenceFinTechreinforcement learning
0 likes · 16 min read
Key Insights from Ant Financial VP Dr. Qi Yuan’s Talk on the Development and Application of Financial Intelligence at CCAI 2017
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 13, 2017 · Artificial Intelligence

How STARK VRP Cuts Chinese Logistics Costs with AI‑Powered Routing

This article explains how Alibaba's Cainiao network built the STARK VRP engine—an AI‑driven, distributed vehicle‑routing solver that supports dozens of VRP variants, leverages metaheuristics, parallel island models, and deep reinforcement learning to dramatically reduce fleet size and travel distance in Chinese logistics.

AILogistics OptimizationMetaheuristics
0 likes · 8 min read
How STARK VRP Cuts Chinese Logistics Costs with AI‑Powered Routing
21CTO
21CTO
Jun 29, 2017 · Artificial Intelligence

Why Machine Learning Mirrors Human Learning: From Features to Reinforcement

The article explores how machine learning models emulate human learning by converting diverse real‑world descriptions into numerical features, illustrating concepts such as one‑hot encoding, supervised, unsupervised, and reinforcement learning, and emphasizing the importance of mapping inputs to outputs for intelligent systems.

AI conceptsOne-hot encodingSupervised Learning
0 likes · 14 min read
Why Machine Learning Mirrors Human Learning: From Features to Reinforcement
Qunar Tech Salon
Qunar Tech Salon
Apr 27, 2017 · Artificial Intelligence

LSTM‑Jump: Learning to Skim Text for Faster Sequence Modeling

The paper introduces LSTM‑Jump, a reinforcement‑learning‑trained LSTM variant that can dynamically skip irrelevant tokens, achieving up to six‑fold speed‑ups over standard sequential LSTMs while maintaining or improving accuracy on various NLP tasks such as sentiment analysis, document classification, and question answering.

LSTMNLPSequence Modeling
0 likes · 7 min read
LSTM‑Jump: Learning to Skim Text for Faster Sequence Modeling
21CTO
21CTO
Apr 19, 2017 · Artificial Intelligence

How Alibaba Transformed E‑Commerce Search with Real‑Time AI and Reinforcement Learning

Alibaba’s e‑commerce search engine evolved over three years from offline batch models to a sophisticated AI-driven system that integrates real‑time feature ingestion, online learning, deep and reinforcement learning, enabling dynamic personalization and decision‑making that boosts conversion during high‑traffic events like Double 11.

AIReal-Time Computinge-commerce
0 likes · 15 min read
How Alibaba Transformed E‑Commerce Search with Real‑Time AI and Reinforcement Learning
Architect
Architect
Mar 10, 2016 · Artificial Intelligence

Monte Carlo Tree Search (MCTS): Principles, Algorithms, Advantages, and Applications

This article explains Monte Carlo Tree Search (MCTS), covering its origin in AlphaGo, fundamental algorithm steps, node‑selection strategies such as UCB, strengths and weaknesses, enhancements, historical background, and recent research developments in artificial intelligence.

Artificial IntelligenceMCTSMonte Carlo Tree Search
0 likes · 12 min read
Monte Carlo Tree Search (MCTS): Principles, Algorithms, Advantages, and Applications
dbaplus Community
dbaplus Community
Mar 9, 2016 · Artificial Intelligence

How AlphaGo’s Deep Neural Networks Achieve Human‑Level Go Mastery

This article breaks down AlphaGo’s breakthrough architecture—four specialized neural‑network modules, Monte‑Carlo Tree Search, and deep reinforcement learning—to explain how the system moved from imitation learning to self‑improvement and ultimately defeated top human Go players.

AlphaGoGo AIMonte Carlo Tree Search
0 likes · 15 min read
How AlphaGo’s Deep Neural Networks Achieve Human‑Level Go Mastery
Architects Research Society
Architects Research Society
Oct 4, 2015 · Artificial Intelligence

Bayesian Thinking on Your Feet: Embedding Generative Models in Reinforcement Learning for Sequentially Revealed Data

This NSF‑funded project aims to develop algorithms that incrementally process partially observed data, integrating generative models with reinforcement‑learning policies to decide when to act, applied to simultaneous machine translation and quiz‑bowl style question answering.

Generative Modelsbayesian inferencemachine translation
0 likes · 4 min read
Bayesian Thinking on Your Feet: Embedding Generative Models in Reinforcement Learning for Sequentially Revealed Data
Baidu Tech Salon
Baidu Tech Salon
Sep 22, 2014 · Artificial Intelligence

How Baidu’s Bingo AI Cracked the Go Challenge with Novel Algorithms

After decades of being deemed a 'century‑long' AI challenge, Baidu’s Bingo system achieved amateur‑to‑professional level Go play by introducing optimized Monte‑Carlo tree search, a weakened Alpha‑Beta hybrid, and massive supervised learning, demonstrating how breakthroughs in game AI can ripple into broader Baidu products.

Artificial IntelligenceBaiduGo AI
0 likes · 8 min read
How Baidu’s Bingo AI Cracked the Go Challenge with Novel Algorithms