Transport Layer Security (TLS) is a cryptographic protocol that provides secure communication over computer networks, including the internet. It is the successor to the Secure Socket Layer (SSL) protocol. TLS ensures the confidentiality, integrity, and authenticity of data transmitted between client-server applications. Here are key aspects of TLS: Encryption: TLS uses encryption algorithms to protect …
Secure Socket Layer (SSL) is a cryptographic protocol designed to provide secure communication over the internet. It ensures the confidentiality, integrity, and authenticity of data transmitted between a client and a server. SSL has been succeeded by the Transport Layer Security (TLS) protocol, but the term “SSL” is still commonly used to refer to both …
Internet security protocols are essential for ensuring the confidentiality, integrity, and availability of data transmitted over the internet. They provide a framework for secure communication between devices and protect against various threats such as eavesdropping, data tampering, and unauthorized access. Here are some basic concepts of internet security protocols: Secure Sockets Layer (SSL) and Transport …
Agents are autonomous entities that can perceive their environment, reason about it, and take actions to achieve specific goals or objectives. They are a fundamental concept in the field of artificial intelligence (AI) and play a central role in building intelligent systems. An agent can be thought of as a software or hardware entity that …
Introduction to Agents and their Application in Intelligent System Read More »
A Bayesian network, also known as a belief network or probabilistic graphical model, is a graphical representation of probabilistic relationships among variables. It provides a compact and intuitive way to model complex systems by capturing the dependencies between variables and their conditional probabilities. In a Bayesian network, variables are represented as nodes, and the relationships …
Dempster-Shafer theory, also known as belief theory or evidence theory, is a mathematical framework for reasoning and decision-making under uncertainty. It provides a way to combine and manage evidence from multiple sources, even when the evidence may be uncertain or conflicting. Dempster-Shafer theory extends classical probability theory by allowing for the representation and combination of …
Bayesian theory, also known as Bayesian inference or Bayesian statistics, is a mathematical framework for updating beliefs or probabilities based on new evidence or data. It provides a principled approach to reasoning and making decisions under uncertainty by combining prior knowledge with observed evidence. The core idea of Bayesian theory is to represent uncertain quantities, …
Probabilistic methods refer to approaches that utilize probability theory to model, reason, and make decisions under uncertainty. These methods provide a framework for quantifying and managing uncertainty by assigning probabilities to different events or outcomes. By incorporating probabilistic reasoning, these methods enable a more robust and quantitative analysis of uncertain situations. Here are some key …
Fuzzy logic is a mathematical framework used to handle and reason with uncertainty and imprecision in information. It provides a way to represent and manipulate vague or fuzzy concepts that do not have precise boundaries. Fuzzy logic extends classical binary logic by allowing intermediate degrees of truth or membership between true and false. In classical …
Uncertainty management in expert systems refers to the techniques and methods employed to handle and reason about uncertain or incomplete information within the knowledge base of an expert system. Expert systems are computer-based systems that aim to emulate human expertise in a specific domain by capturing knowledge and using it to make decisions or provide …
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