Probabilistic Reasoning - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit II: Probabilistic Reasoning
A agent working in real world environment almost never has access to whole truth about its environment. Therefore, agent needs to work under uncertainity.
Constraint Satisfaction Problems (CSP) - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit I(f): Constraint Satisfaction Problems (CSP)
CSP are problems whose state and goal test conform to a standard structured and very simple representation. CSP's are defined using set of variables and set of constraints on those variables.
Constraint Satisfaction Problems (CSP) - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit I(f): Constraint Satisfaction Problems (CSP)
If we apply BFS to generic CSP problems then we can notice that the branching factor at the top level is 'nd', because any of 'd' values can be assigned to any of 'n' variables.
Constraint Satisfaction Problems (CSP) - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit I(f): Constraint Satisfaction Problems (CSP)
There have been many advances in how constraint solvers search for solutions. We look first at a pre-processing step which can greatly improve efficiency by pruning the search space, namely arc-consistency.
Constraint Satisfaction Problems (CSP) - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit I(f): Constraint Satisfaction Problems (CSP)
While selecting unassigned variable for computation if we look at some of the constraints earlier in the search (or even before search begins), we can drastically reduce search space.
Constraint Satisfaction Problems (CSP) - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit I(f): Constraint Satisfaction Problems (CSP)
This problem, first posed in a German chess magazine almost 150 years ago, requires that 8 queens be placed on an 8 x 8 chessboard in such a way that no two queens attack each other, i.e. no two queens occupy the same row, column, or diagonal.
Constraint Satisfaction Problems (CSP) - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit I(f): Constraint Satisfaction Problems (CSP)
Constraint satisfaction problem has various states and goal test, a tranditional problem has been converted into standard structured and very simple "representation".
Adversarial search - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit I(e): Adversarial search
Explain perfect decisions in game playing
Adversarial search - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit I(e): Adversarial search
In a game of chance we can add extra level of chance nodes in game search tree. These nodes have successors which are the outcomes of random element.
Adversarial search - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit I(e): Adversarial search
Stochastic games represent dynamic interactions in which the environment changes in response to players' behavior. Scientist Shapley says, "In a stochastic game the play proceeds by steps from position to position, according to transition probabilities controlled jointly by the two players"
Adversarial search - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit I(e): Adversarial search
While developing game playing applications the incremental approach can be taken. First stage is, human plays against human. In this stage program serve as a representation.
Adversarial search - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit I(e): Adversarial search
Games with a certain element of chance are often more interesting than those without chance, and many games involve rolling dice, tossing a coin or something similar.