Artificial intelligence: a modern approach
Authors: Dr. Anil Kumar, Sivasubramanian Balasubramanian, Dr. Haewon Byeon
The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical ...
📅 Published: 1995
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🌐 Source: OpenAlex
📊 Citations: 22254
Probability Judgement in Artificial Intelligence
Authors: Glenn Shafer
This paper is concerned with two theories of probability judgment: the Bayesian theory and the theory of belief functions. It illustrates these theories with some simple examples and discusses some of the issues that arise when we try to implement them in expert systems. The Bayesian theory is well known; its main ideas go back to the work of Thomas Bayes (1702-1761). The theory of belief function...
A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When?
Authors: Subrato Bharati, M. Rubaiyat Hossain Mondal, Prajoy Podder
Artificial intelligence (AI) models are increasingly finding applications in the field of medicine. Concerns have been raised about the explainability of the decisions that are made by these AI models. In this article, we give a systematic analysis of explainable artificial intelligence (XAI), with a primary focus on models that are currently being used in the field of healthcare. The literature s...
The Bayesian Reflex: A Predictive Coding Engine for Artificial Intelligence
Authors: Sourabh Bhattacharya
Predictive coding offers a powerful theory of cortical computation, but corresponding scalable algorithmic implementations for artificial intelligence have remained elusive. This paper introduces the Bayesian reflex, a computational framework that directly instantiates predictive coding through three pillars: belief maintenance via hierarchical generative models, sequential Bayesian updating via p...
Games for Artificial Intelligence Research: A Review and Perspectives
Authors: Chengpeng Hu, Yunlong Zhao, Ziqi Wang
Games have been the perfect test-beds for artificial intelligence research for the characteristics that widely exist in real-world scenarios. Learning and optimisation, decision making in dynamic and uncertain environments, game theory, planning and scheduling, design and education are common research areas shared between games and real-world problems. Numerous open-source games or game-based envi...