<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Cognitive Science on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/cognitive-science/</link><description>Recent content in Cognitive Science on English AI Terms Dictionary</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 18 Jul 2026 11:44:44 +0000</lastBuildDate><atom:link href="https://terms-en.ai-term-hub.com/en/tags/cognitive-science/index.xml" rel="self" type="application/rss+xml"/><item><title>Situated</title><link>https://terms-en.ai-term-hub.com/en/terms/situated/</link><pubDate>Sat, 18 Jul 2026 10:15:35 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/situated/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>In artificial intelligence, &amp;lsquo;situated&amp;rsquo; refers to agents that are embedded in an environment and interact with it in real-time. Unlike abstract problem-solvers, situated agents must process sensory input and execute actions while being constrained by their immediate surroundings. This concept is central to embodied cognition and robotics, emphasizing that intelligence is not just computational but arises from the dynamic interaction between the agent and its context. It challenges traditional symbolic AI by requiring systems to handle ambiguity, noise, and partial information inherent in real-world settings.&lt;/p></description></item><item><title>Knowledge level</title><link>https://terms-en.ai-term-hub.com/en/terms/knowledge_level/</link><pubDate>Sat, 18 Jul 2026 10:03:55 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/knowledge_level/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>Coined by Allen Newell, the knowledge level analyzes intelligent systems based on their beliefs and goals, independent of their physical implementation. It separates the rationality of an agent&amp;rsquo;s actions from the specific algorithms used to achieve them. This abstraction allows designers to specify system requirements purely in terms of knowledge and intent, facilitating modular and scalable AI development.&lt;/p>
&lt;h3 id="summary">Summary&lt;/h3>
&lt;p>An abstract design perspective focusing on what an agent knows rather than how it processes information internally.&lt;/p></description></item><item><title>Developmental Robotics</title><link>https://terms-en.ai-term-hub.com/en/terms/developmental_robotics/</link><pubDate>Sat, 18 Jul 2026 09:55:14 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/developmental_robotics/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>Developmental robotics draws inspiration from human cognitive development to create robots that learn autonomously over time. Instead of pre-programming all behaviors, these systems use mechanisms like imitation, reinforcement learning, and intrinsic motivation to progressively acquire motor, perceptual, and social skills. The goal is to build adaptable agents capable of lifelong learning in dynamic, unstructured environments.&lt;/p>
&lt;h3 id="summary">Summary&lt;/h3>
&lt;p>An interdisciplinary field studying how robots can acquire complex skills through interaction with their environment and caregivers.&lt;/p></description></item><item><title>Belief–desire–intention model</title><link>https://terms-en.ai-term-hub.com/en/terms/beliefdesireintention_model/</link><pubDate>Sat, 18 Jul 2026 09:48:06 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/beliefdesireintention_model/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>The Belief-Desire-Intention (BDI) model is a cognitive architecture for designing autonomous agents that make rational decisions. Beliefs represent the agent&amp;rsquo;s knowledge about the world, desires are its goals, and intentions are the specific plans committed to achieving those goals. This model helps create agents that can dynamically adapt to changing environments by updating their beliefs, refining their desires, and revising their intentions. It is foundational in multi-agent systems and intelligent automation.&lt;/p></description></item><item><title>Artificial psychology</title><link>https://terms-en.ai-term-hub.com/en/terms/artificial_psychology/</link><pubDate>Sat, 18 Jul 2026 09:46:35 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/artificial_psychology/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>Artificial psychology is an interdisciplinary domain focusing on the design and implementation of cognitive architectures in AI systems. It draws from cognitive science and psychology to model human mental states, reasoning, learning, and emotion within computational frameworks. The goal is to create AI that does not just process data logically but exhibits behaviors resembling human cognition, including intuition, creativity, and adaptive learning, thereby making interactions more natural and intelligible to human users.&lt;/p></description></item><item><title>Artificial Inventor Project</title><link>https://terms-en.ai-term-hub.com/en/terms/artificial_inventor_project/</link><pubDate>Sat, 18 Jul 2026 09:46:04 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/artificial_inventor_project/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>The Artificial Inventor Project is an interdisciplinary research effort aimed at understanding and replicating the cognitive mechanisms behind human creativity and invention. It seeks to build AI systems capable of generating novel ideas, solving ill-defined problems, and mimicking the intuitive leaps often seen in human inventors. By studying how humans combine disparate concepts to form new solutions, this project contributes to the broader field of computational creativity, aiming to create tools that assist rather than replace human innovators in design and engineering tasks.&lt;/p></description></item></channel></rss>