Robot Control 4.6.0
Robot simulation to help you with your studies. A robot is an intelligent agent that perceives, reasons, and acts in time in an environment. It acts to achieve its assigned goals and at the same time avoids getting into undesired states. The robot applet provides a simulation of a robot perceiving and acting under the control of a set of customizable robot controller functions.Requirements:* Java
Price: USD $0.00;
File Size: 429 KB;
Graph Searching 4.5.0
Search is an important part of AI; many problems can be cast as the problem of finding a path in a graph. Graph Searching is a graph-searching tool, it is designed to help you learn about different search strategies.Graphs consist of a set of nodes which are connected via a set of edges. These structures are common in problems arising in Computational Intelligence and Computer Science in general. This applet examines the problem of efficiently...
Price: USD $0.00;
File Size: 240 KB;
Decision Trees 4.3.8
Create decision trees to help you with your work. Learning is the capability to improve one's behaviour based on experience and represents an essential element of computational intelligence. Decision trees are a simple yet successful technique for supervised classification learning. This applet demonstrates how to build a decision tree using a training dataset and then use the tree to classify unseen examples in a test dataset.This applet...
Stochastic Local Search Based CSP Solver 4.6.0
Stochastic Local Search Based CSP Solver use stochastic local search algorithms to solve constraint satisfaction problems. Constraint satisfaction problems (CSPs) are pervasive in AI problems. A constraint satisfaction problem is the problem of assigning values to variables that satisfy some constraints. This CSP solver uses stochastic local search algorithms to attempt to find assignments to the variables which satisfy the constraints using...
Belief and Decision Networks 5.1.9
View and solve Bayesian Nets fast and easy. Bayesian Belief and Decision Networks help you solve Bayesian Nets. It has a robust variable elimination algorithm, and allows users to create their own networks and customize the domains and probabilities.Bayesian Networks, also called Belief or Causal Networks, are a part of probability theory and are important for reasoning in AI. They are a strong tool for modelling decision-making under...
Consistency Based CSP Solver 4.6.1
Consistency Based CSP Solver create and solve constraint satisfaction problem. Constraint satisfaction problems (CSPs) are pervasive in AI problems. A constraint satisfaction problem is the problem of assigning values to variables that satisfy some constraints. This constraint satisfaction problem solver (arc consistency) tool is designed to help you learn about solving CSPs with a systematic search technique called arc consistency.Consistency...
Definite Clause Deduction 4.2.8
Analyze deduction algorithms. Definite Clause Deduction demonstrate various deduction algorithms, from the SLD resolution used by Prolog to the user manually unifying clauses.Every representation and reasoning system needs a proof procedure in order to be complete. The purpose of this tool is to illustrate how the process of answer extraction within a knowledge base can be cast as a search problem. The deduction tool uses a language similar to...