Exploring Probabilistic Generative, Discriminative, Bayesian in AI Algorithms

Probabilistic Approaches or Algorithms play a vital role in Artificial Intelligence and Cognitive Science for generating, reasoning, decisions (simple and complex). This article covers Generative, Discriminative and Reasoning with Bayes Networks approaches. The other approaches will be covered in the sequence to this article.

Contents

1. Introduction
2. Generative / Discriminative Algorithms
3. Bayes Networks

Introduction

Probability Theory is very simple and extended to apply on many concepts like Distributions, Estimation, Generating, Reasoning, Sampling, etc., Probability Theory can be applied to worlds with objects and relations.

Independence and Conditional Independence relationships among variables reduce the number of…

Explores fields and concepts required for Quantum Computing

Contents

Explored major fields and topics. Starting with explaining a bit introduction of Classical Computers, Quantum Computing, Qubits — Basis state, State, Statevector, QC Works on, Advantage over Traditional Computing, Prerequisites, Fields or Subject Contributing, Quantum Properties, QC Serving Fields, QC Providers, Limitations of QC.

Starting with Classical Computers.

Classical Computers: Traditional Computers work both Theory (Turing Machines) and practice (PCs, laptops, tablets, smartphones, etc.,) on the basis of the laws of classical physics, specifically by utilizing the flow of electricity.

Bits: Traditional computing bits are in a state of either “0” or…

Detection of planets in a new way using Artificial Intelligence

This article, describing how to use AI for the detection of Exoplanets. AI is being used in astronomical applications and one of the major applications is Exoplanet detection.

The audience for this article are physicists or researchers, who are interested to use AI as a tool for astronomical projects or applications and it resembles Comet, Asteroid detection as well.

The objective of this article is to introduce Exoplanets and applying in Machine Learning and Deep Learning Algorithms. Introducing Exoplanets, Data, ML/DL algorithms, and results.

Contents

1. Exoplanets — Section I
2. Artificial Intelligence…

Using Cognitive Science and Physics

This article explores the usages of Cognitive Science and Physics to combine with Artificial Intelligence. The power of AI is not only limited to Machines or programs or vehicles or smart systems, it enlarges with various domains to overcome the difficulties of hard environments where it is highly complicated or unable to dig in such kinds of environments. In order to extend its presence in vast fields such as astronomy and particle/nuclear physics is remarkable. To get or mimic human intelligence not almost but somehow can achieve by combining AI with Cognitive Science.

This article…

Understand Agents (Bots, Robots, Programs) and Environment (working place).

Exploring Deep Learning, RL , NLP, Perception and Integrating Modules/Sub-fields.

Introducing & Exploring Problem Solving , Planing , Reasoning & Machine learning.

Due to readability issues divided this article into two parts.

Learn in an interact way

Reinforcement Learning is part of Machine Learning and an agent learns on its own by interacting with Environment. RL does not require a data set.

Reinforcement Learning history and MDP is covered in more detail due to its popularity and more advanced research today, which is applicable in major applications like Autonomous Vehicles, Robotics, unknown and hard environments.

This article explores MDP & RL methods of Dynamic Programming along with examples. This article is particularly for beginners and those who want to know how RL is coming into picture. Due to non-deterministic actions of agents…