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Goal programming is a branch of multiobjective optimization, which in turn is a branch of multi-criteria decision analysis (MCDA). It can be thought of as an extension or generalisation of linear programming to handle multiple, normally conflicting objective measures.
Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute optimization) is an area of multiple-criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously.
GOAL is an agent programming language for programming cognitive agents.GOAL agents derive their choice of action from their beliefs and goals. The language provides the basic building blocks to design and implement cognitive agents by programming constructs that allow and facilitate the manipulation of an agent's beliefs and goals and to structure its decision-making.
Intentional elements are: goal, soft goal, task, belief and resource. Goal is condition or situation that can be achieved or not. Goal is used to define the functional requirements of the system. In GRL notation goal is represented by a rounded rectangle with the goal name inside. Task is used to represent different ways of how to accomplish goal.
A goal model is an element of requirements engineering that may also be used more widely in business analysis. Related elements include stakeholder analysis , context analysis , and scenarios , [ 1 ] among other business and technical areas.
Multi-objective linear programming is a subarea of mathematical optimization. A multiple objective linear program (MOLP) is a linear program with more than one objective function. An MOLP is a special case of a vector linear program .
Figure 1. Finding the shortest path in a graph using optimal substructure; a straight line indicates a single edge; a wavy line indicates a shortest path between the two vertices it connects (among other paths, not shown, sharing the same two vertices); the bold line is the overall shortest path from start to goal.
The belief–desire–intention software model (BDI) is a software model developed for programming intelligent agents.Superficially characterized by the implementation of an agent's beliefs, desires and intentions, it actually uses these concepts to solve a particular problem in agent programming.