Agent
وكيل
نظام ذكاء اصطناعي يُدرك بيئته ويستدلّ حول أهدافه وينفّذ أفعالاً لتحقيقها — عادةً من خلال حلقات تفاعل تكرارية بين التفكير والفعل والملاحظة.
An AI system that perceives its environment, reasons about goals, and takes actions to achieve them — typically through iterative think-act-observe interaction loops.
Also translated asالعميل المستقل، الفاعل الآلي، الفاعل المستقل، الوكيل البرمجي، الوكيل الذكي
First appears in this corpus in: Computing Machinery and Intelligence (1950)
Appears in these papers
- Asynchronous Methods for Deep Reinforcement Learning2016in the sky ✦
- AI Safety via Debate2018in the sky ✦
- Concrete Problems in AI Safety2016in the sky ✦
- Conservative Q-Learning for Offline Reinforcement Learning2020in the sky ✦
- A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence1956in the sky ✦
- Continuous Control with Deep Reinforcement Learning2015in the sky ✦
- Deep Reinforcement Learning from Human Preferences2017in the sky ✦
- Deep Reinforcement Learning with Double Q-Learning2016in the sky ✦
- Human-Level Control Through Deep Reinforcement Learning2015in the sky ✦
- Dueling Network Architectures for Deep Reinforcement Learning2016in the sky ✦
- High-Dimensional Continuous Control Using Generalized Advantage Estimation2016in the sky ✦
- A Generalist Agent2022in the sky ✦
- Generative Agents: Interactive Simulacra of Human Behavior2023in the sky ✦
- Generative Agents: Interactive Simulacra of Human Behavior2023in the sky ✦
- First Return, Then Explore2021in the sky ✦
- Hindsight Experience Replay2017in the sky ✦
- HuggingGPT: Solving AI Tasks with ChatGPT and Its Friends in Hugging Face2023in the sky ✦
- HuggingGPT: Solving AI Tasks with ChatGPT and Its Friends in Hugging Face2023in the sky ✦
- Curiosity-Driven Exploration by Self-Supervised Prediction2017in the sky ✦
- MuZero: Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model2020in the sky ✦
- Between MDPs and Semi-MDPs — A Framework for Temporal Abstraction in Reinforcement Learning1999in the sky ✦
- Policy Gradient Methods for Reinforcement Learning with Function Approximation1999in the sky ✦
- Proximal Policy Optimization Algorithms2017in the sky ✦
- Prioritized Experience Replay2015in the sky ✦
- Q-Learning1992in the sky ✦
- Rainbow: Combining Improvements in Deep Reinforcement Learning2018in the sky ✦
- ReAct: Synergizing Reasoning and Acting in Language Models2023in the sky ✦
- ReAct: Synergizing Reasoning and Acting in Language Models2023in the sky ✦
- Reflexion: Language Agents with Verbal Reinforcement Learning2023in the sky ✦
- Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning1992in the sky ✦
- RT-1: Robotics Transformer for Real-World Control at Scale2022in the sky ✦
- Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor2018in the sky ✦
- Sparks of Artificial General Intelligence: Early Experiments with GPT-42023in the sky ✦
- Computing Machinery and Intelligence1950in the sky ✦
- Voyager: An Open-Ended Embodied Agent with Large Language Models2023in the sky ✦
- Voyager: An Open-Ended Embodied Agent with Large Language Models2023in the sky ✦
- WebArena: A Realistic Web Environment for Building Autonomous Agents2023in the sky ✦
- WebArena: A Realistic Web Environment for Building Autonomous Agents2023in the sky ✦
- World Models2018in the sky ✦
- World Models2018in the sky ✦