Define Successor function.

Define Successor function.
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Answer :

A value can be assigned to any unassigned variable, provided that does not conflict with previously assigned variables.
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Related questions

A game can be formally defined as a kind of search problem with the following components. a) Initial State b) Successor Function c) Terminal Test d) All of the mentioned

Description : A game can be formally defined as a kind of search problem with the following components. a) Initial State b) Successor Function c) Terminal Test d) All of the mentioned

Last Answer : d) All of the mentioned

What among the following constitutes to the incremental formulation of CSP? a) Path cost b) Goal cost c) Successor function d) All of the mentioned

Description : What among the following constitutes to the incremental formulation of CSP? a) Path cost b) Goal cost c) Successor function d) All of the mentioned

Last Answer : d) All of the mentioned

The Set of actions for a problem in a state space is formulated by a ___________ a) Intermediate states b) Initial state c) Successor function, which takes current action and returns next immediate state d) None of the mentioned

Description : The Set of actions for a problem in a state space is formulated by a ___________ a) Intermediate states b) Initial state c) Successor function, which takes current action and returns next immediate state d) None of the mentioned

Last Answer : c) Successor function, which takes current action and returns next immediate state

The minimax algorithm computes the minimax decision from the current state. It uses a simple recursive computation of the minimax values of each successor state, directly implementing the defining equations. The recursion proceeds all the way down to the leaves of the tree, and then the minimax values are backed up through the tree as the recursion unwinds. a) True b) False

Description : The minimax algorithm computes the minimax decision from the current state. It uses a simple recursive computation of the minimax values of each successor state, directly implementing the defining equations. The ... are backed up through the tree as the recursion unwinds. a) True b) False

Last Answer : a) True

A genetic algorithm (or GA) is a variant of stochastic beam search in which successor states are generated by combining two parent states, rather than by modifying a single state. a) True b) False

Description : A genetic algorithm (or GA) is a variant of stochastic beam search in which successor states are generated by combining two parent states, rather than by modifying a single state. a) True b) False

Last Answer : a) True

Define Heuristic function, h (n).

Description : Define Heuristic function, h (n).

Last Answer :  h (n) is defined as the estimated cost of the cheapest path from node n to a goal node. 

Define Evaluation function, f(n).

Description : Define Evaluation function, f(n).

Last Answer : A node with the lowest evaluation is selected for expansion, because evaluation measures distance to the goal.

Define Agent Function.

Description : Define Agent Function.

Last Answer : It is a mathematical description which deals with the agent’s behavior that maps the given percept sequence into an action.

The initial state and the legal moves for each side define the __________ for the game. a) Search Tree b) Game Tree c) State Space Search d) Forest

Description :  The initial state and the legal moves for each side define the __________ for the game. a) Search Tree b) Game Tree c) State Space Search d) Forest

Last Answer : b) Game Tree

Define Information Extraction.

Description : Define Information Extraction.

Last Answer : It is a process of creating database entries by skimming a text and looking for occurrences of a particular class of object.

Define Information Retrieval (IR).

Description : Define Information Retrieval (IR).

Last Answer :  IR is the task of finding documents that are relevant to user’s need for information. 

Define Segmentation?

Description : Define Segmentation?

Last Answer :  The process of finding the words boundaries in a text with no spaces. 

Define Discourse understanding.

Description : Define Discourse understanding.

Last Answer :  A discourage is any string of language usually one that is more than one sentence long. 

Define Disambiguation.

Description : Define Disambiguation.

Last Answer : The speaker’s aim is to communicate some words in utterance and hearer work is to get back the meaning of the world from the knowledge of situation.

Define Ambiguity.

Description : Define Ambiguity.

Last Answer :  The sentence that does not provide exact meaning are called ambiguous sentence. 

Define Sub categorization.

Description : Define Sub categorization.

Last Answer : E 2 eliminates VP by mentioning which phrases can allow which verbs which are known as sub categorization.

Define DCG.

Description : Define DCG.

Last Answer : The method of rewriting the existing rules in the grammar by the method of augmentation is called as DCG (Define Clause Grammar). 

Define Augmentation.

Description : Define Augmentation.

Last Answer : The process of adding the existing rules of a grammar instead of introducing new rules. It is called Augmentation.

Define Bottom up parsing.

Description : Define Bottom up parsing.

Last Answer :  We start from the leaf nodes (i.e.) with the words and search for a tree with root S. 

Define Top down parsing.

Description : Define Top down parsing. 

Last Answer :  It starts with root node S and search for a tree that has the words as it leaves. 

Define Parsing.

Description : Define Parsing.

Last Answer : Parsing is the process of finding a parse tree for a given input string. It is also known as syntactic analysis.

Define Semantic Interpretation.

Description : Define Semantic Interpretation.

Last Answer :  The process of extracting the meaning of an utterance an expression in some representation language. 

Define Formal Language.

Description : Define Formal Language.

Last Answer :  A formal language is defined as a set of strings of terminal symbols. It is called as words. 

Define Language.

Description : Define Language. 

Last Answer :  Language enables us to communicate most of what we have observed about the environment. 

Define Communication.

Description : Define Communication.

Last Answer : Communication is the international exchange of information brought about by the production and perception of signs drawn from a shared system of conventional signs.

Define Reification.

Description : Define Reification.

Last Answer : The process of treating something abstract and difficult to talk about as though it were concrete and easy to talk about is called as reification. 

Define Similarity nets.

Description : Define Similarity nets.

Last Answer : Similarity net is an approach for arranging models. Similarity net is a representation in which nodes denotes models, links connect similar models and links are tied to different descriptions. 

Define conditional planning.

Description : Define conditional planning.

Last Answer : Conditional planning is a way in which the incompleteness of information is incorporated in terms of adding a conditional step, which involves if – then rules.

Define a consistent plan.

Description : Define a consistent plan.

Last Answer : A consistent plan is one in which there are no contradictions in the ordering or binding constraints. 

Define a complete plan.

Description : Define a complete plan.

Last Answer : A complete plan is one in which every precondition of every step is achieved by some other step. 

Define a solution

Description : Define a solution

Last Answer : A solution is defined as a plan that an agent can execute and that guarantees the achievement of goal. 

Define planning.

Description : Define planning.

Last Answer : Planning can be viewed as a type of problem solving in which the agent uses beliefs about actions and their consequences to search for a solution.

Define TD.

Description : Define TD.

Last Answer : Temporal Difference learning: The key of TD is to use the observed transitions to adjust the values of the observed states so that they agree with the constraint equations.

Define Active Learning.

Description : Define Active Learning.

Last Answer : The agent must learn what to do. An agent must experience as much as possible of its environment in order to learn how to behave in it.

Define Passive learning.

Description : Define Passive learning.

Last Answer : The agent’s policy is fixed and the task is to learn the utilities of states, this could also involve learning a model of the environment.

Define Neural Networks.

Description : Define Neural Networks.

Last Answer : It consists of nodes or units connected by directed links. A link propagates the activation. Each link has a numeric weight which determines the strength and sign of the connection.

Define EM.

Description : Define EM.

Last Answer : Expectation Maximization: the idea of EM is to pretend that we know the parameters of the model and then to infer the probability that each data point belongs to each component. After that we ... where each component is fitted to the entire data set with each point weighted by the probability. 

Define sum of squared errors.

Description : Define sum of squared errors.

Last Answer : The difference between the actual value yj and the predicated value ( θ1 xj + θ2 ) so E is the sum of squared errors. 

Define Naïve Bayes model.

Description : Define Naïve Bayes model.

Last Answer : In this model, the “class” variable C is the root and the “attribute” variable XI are the leaves. This model assumes that the attributes are conditionally independent of each other, given the class.

Define MDL.

Description : Define MDL.

Last Answer : The MDL (Maximum Description Length), is a learning method which attempts to minimize the size of the hypotheses and data encodings rather than work with probabilities.

Define MAP.

Description : Define MAP.

Last Answer : Maximum A Posteriori. A very common approximation is to make predictions based on single most probable hypotheses. This is MAP. 

Define Bayesian Learning.

Description : Define Bayesian Learning.

Last Answer : It calculates the probability of each hypotheses, given the data and makes predictions on that basis, (i.e.) predictions are made by using all the hypotheses, weighted by their probabilities rather than by using just single “best” hypotheses.

Define constructive induction algorithm.

Description : Define constructive induction algorithm.

Last Answer :  Algorithms that can generate new predicates are called constructive induction algorithms. 

Define Inductive Logic Programming (ILP).

Description : Define Inductive Logic Programming (ILP).

Last Answer : ILP techniques perform KBIL on knowledge that is expressed in first order logic. ILP methods can learn relational knowledge that is not expressible in attribute based systems.

Define knowledge based Inductive learning.

Description : Define knowledge based Inductive learning.

Last Answer : KBIL algorithm finds inductive hypotheses that explain sets of observations with the help of background knowledge.

Define RBL.

Description : Define RBL.

Last Answer : Relevance based Learning; the prior knowledge background concerns the relevance of a set of features to the goal predicate. This knowledge together with the observations, Allows the agent to ... ^ Description |= classifications,  Background ^ Description ^ classifications |= Hypothesis.

Define EBL.

Description : Define EBL.

Last Answer : Explanation based learning, from the prior knowledge (or) information; we can infer a general rule. This kind of generalization process called explanation based learning (or) EBL.

Define Boundary set.

Description : Define Boundary set.

Last Answer :  Each boundary will not be a point but rather a set of hypotheses called a Boundary set. 

Define Decision list.

Description : Define Decision list.

Last Answer : It is a logical expression of a restricted form, It consists of a series of tests, each of which conjunction of literals. If test succeeds, value is returned. If test fails, processing continues with the next test in the list.

Define PAC – Learning Algorithm.

Description : Define PAC – Learning Algorithm.

Last Answer : An learning algorithm that return hypotheses that are approximately correct is called PAC learning algorithm.