The Role of Outcome Divergence in Goal
... blocks, the values assigned to the blue, green and red token respectively were $2, $2 and $1, yielding identical expected values for all actions. However, to simulate a dynamic environment, in a subset of blocks, the token values were changed to $2, $1 and $3 respectively, and in yet another subset ...
... blocks, the values assigned to the blue, green and red token respectively were $2, $2 and $1, yielding identical expected values for all actions. However, to simulate a dynamic environment, in a subset of blocks, the token values were changed to $2, $1 and $3 respectively, and in yet another subset ...
Church: a language for generative models
... can be used in body, and is sugar for nested lambdas. Church values include Church expressions, and procedures; if v1 ...vn are Church values the list (v1 ...vn ) is a Church value. A Church environment is a list of pairs consisting of a variable symbol and a value (the variable is bound to the valu ...
... can be used in body, and is sugar for nested lambdas. Church values include Church expressions, and procedures; if v1 ...vn are Church values the list (v1 ...vn ) is a Church value. A Church environment is a list of pairs consisting of a variable symbol and a value (the variable is bound to the valu ...
Mining Incomplete Data with Many Missing Attribute Values
... values: lost and “do not care”. The former interpretation means that an attribute value was originally given, however, currently we have no access to it (e.g., the value was forgotten or erased). For data sets with lost values we try to induce the rule set from known data. The latter interpretation ...
... values: lost and “do not care”. The former interpretation means that an attribute value was originally given, however, currently we have no access to it (e.g., the value was forgotten or erased). For data sets with lost values we try to induce the rule set from known data. The latter interpretation ...
Ordinal Decision Models for Markov Decision Processes
... would affect all the value functions by the same constant. As a side note, the result does not hold anymore for an MDP containing an absorbing state where no action is taken. [23] showed that in an MDP where there is only one non null positive (resp. negative) reward, any positive (resp. negative) w ...
... would affect all the value functions by the same constant. As a side note, the result does not hold anymore for an MDP containing an absorbing state where no action is taken. [23] showed that in an MDP where there is only one non null positive (resp. negative) reward, any positive (resp. negative) w ...
Learning bayesian network structure using lp relaxations Please share
... the cycle relaxation Pcycle . It can be shown that these cycle inequalities are equivalent to the transitivity constraints used in Guo & Schuurmans [2006]. The cycle relaxation is not tight in general for two reasons (see Figure 1). First, cycle inequalities generally provide an outer bound on Pdag ...
... the cycle relaxation Pcycle . It can be shown that these cycle inequalities are equivalent to the transitivity constraints used in Guo & Schuurmans [2006]. The cycle relaxation is not tight in general for two reasons (see Figure 1). First, cycle inequalities generally provide an outer bound on Pdag ...
Presentation
... computers and computer programming: here is a magic black box. You can tell it to do whatever you want, within a certain set of rules, and it will do it; within the confines of the box you are more or less God, your powers limited only by your imagination. But the price of that power is strict disci ...
... computers and computer programming: here is a magic black box. You can tell it to do whatever you want, within a certain set of rules, and it will do it; within the confines of the box you are more or less God, your powers limited only by your imagination. But the price of that power is strict disci ...
Methods of Artificial Intelligence – Fuzzy Logic
... Logic based on fuzzy set is polyvalent, it associates the degree of authenticity to each statement. This is known as the value of membership function (Waterman, 1986). Nowadays it is used in a very wide range of scientific fields; from social and psychological studies and researches to its applicati ...
... Logic based on fuzzy set is polyvalent, it associates the degree of authenticity to each statement. This is known as the value of membership function (Waterman, 1986). Nowadays it is used in a very wide range of scientific fields; from social and psychological studies and researches to its applicati ...
Constraint Programming - What is behind?
... • Generator is merged with the tester, i.e., the validity of the constraint is tested as soon as its respective variables are instantiated. This method is used by the backtracking approach. Backtracking (BT) [20] is a method of solving CSP by incrementally extending a partial solution that specifies ...
... • Generator is merged with the tester, i.e., the validity of the constraint is tested as soon as its respective variables are instantiated. This method is used by the backtracking approach. Backtracking (BT) [20] is a method of solving CSP by incrementally extending a partial solution that specifies ...
Efficient coding and the neural representation of value
... rewards or costs associated with any choice or action, is thus critical to the decision-making process. This fundamental relationship between value and choice is expressed explicitly in economic theory, which defines the expected utility of an object only from an analysis of the choices a decisionma ...
... rewards or costs associated with any choice or action, is thus critical to the decision-making process. This fundamental relationship between value and choice is expressed explicitly in economic theory, which defines the expected utility of an object only from an analysis of the choices a decisionma ...
Preference Handling – An Introductory Tutorial
... many types of decision contexts in which preference handling is required. Each such context bring different demands, and one solution may be great for one context, but less so in another. We believe preference handling settings can be, very roughly, divided into three classes. The first involves onl ...
... many types of decision contexts in which preference handling is required. Each such context bring different demands, and one solution may be great for one context, but less so in another. We believe preference handling settings can be, very roughly, divided into three classes. The first involves onl ...
A Closest Fit Approach to Missing Attribute Values in Preterm Birth
... given case with a missing attribute value, we may look for the closest fitting cases within the same concept, as defined by the case with missing attribute value, or in all concepts, i.e., among all cases. The former algorithm is called concept closest fit, the latter is called global closest fit. S ...
... given case with a missing attribute value, we may look for the closest fitting cases within the same concept, as defined by the case with missing attribute value, or in all concepts, i.e., among all cases. The former algorithm is called concept closest fit, the latter is called global closest fit. S ...
How an Agent Might Think
... The answer X = s1 for the query is intuitively correct. On the other hand, one also receives an answer that the required disjunction is true for s2 solely on the basis of two contradictory facts lr(s2 ), ¬lr(s2 ) which is not really what one would expect. C The above example shows that definition b ...
... The answer X = s1 for the query is intuitively correct. On the other hand, one also receives an answer that the required disjunction is true for s2 solely on the basis of two contradictory facts lr(s2 ), ¬lr(s2 ) which is not really what one would expect. C The above example shows that definition b ...
5. Constraint Satisfaction Problems CSPs as Search Problems
... function R EVISE( csp, Xi , Xj ) returns true iff we revise the domain of Xi revised ← false for each x in Di do if no value y in Dj allows (x ,y) to satisfy the constraint between Xi and Xj then delete x from Di revised ← true return revised Figure 6.3 ...
... function R EVISE( csp, Xi , Xj ) returns true iff we revise the domain of Xi revised ← false for each x in Di do if no value y in Dj allows (x ,y) to satisfy the constraint between Xi and Xj then delete x from Di revised ← true return revised Figure 6.3 ...
www.cs.ubc.ca
... occurred in between), then the fluent MN& has value : in the interval S 1 2 . . This is the opposite convention to the event calculus [Shanahan, 1990]. We want this convention as robots have internal state so that it can affect what they will do; if ...
... occurred in between), then the fluent MN& has value : in the interval S 1 2 . . This is the opposite convention to the event calculus [Shanahan, 1990]. We want this convention as robots have internal state so that it can affect what they will do; if ...
Slides for October 2nd
... A support for a value ai ∈ Di is a value in another domain aj ∈ Dj such that (ai , aj ) ∈ Cij . aj allows for an assignment of ai under the constraint Cij . When using table constraints we can count support for a domain value, pruning when the number of supports left drops to zero. For intensional c ...
... A support for a value ai ∈ Di is a value in another domain aj ∈ Dj such that (ai , aj ) ∈ Cij . aj allows for an assignment of ai under the constraint Cij . When using table constraints we can count support for a domain value, pruning when the number of supports left drops to zero. For intensional c ...
av -bv -c - IDA.LiU.se
... Pick one of the prop symbols, e.g. p, and construct one modification of A for each of the two truth-values. Obtain A[p] by removing all clauses containing p and by removing -p in all clauses where they occur. Similarly for A[-p]. ...
... Pick one of the prop symbols, e.g. p, and construct one modification of A for each of the two truth-values. Obtain A[p] by removing all clauses containing p and by removing -p in all clauses where they occur. Similarly for A[-p]. ...
PDF - The Insight Centre for Data Analytics
... Because of the dynamism and uncertainty associated with many real life problems, these problems and their associated Constraint Satisfaction Problem (CSP) models may change over time; thus an earlier solution found for the latter may become invalid. Moreover, many approaches proposed in the literatu ...
... Because of the dynamism and uncertainty associated with many real life problems, these problems and their associated Constraint Satisfaction Problem (CSP) models may change over time; thus an earlier solution found for the latter may become invalid. Moreover, many approaches proposed in the literatu ...
DUCT: An Upper Confidence Bound Approach to Distributed
... depend on a common variable, a partial order on the variables could make the optimization more efficient. This can be obtained from the constraint graph by finding a pseudotree (Freuder and Quinn 1985) of the graph. A pseudo-tree G ′ is simply a rooted directed spanning tree on G. In the algorithms ...
... depend on a common variable, a partial order on the variables could make the optimization more efficient. This can be obtained from the constraint graph by finding a pseudotree (Freuder and Quinn 1985) of the graph. A pseudo-tree G ′ is simply a rooted directed spanning tree on G. In the algorithms ...
PDF only - at www.arxiv.org.
... max point and then stabilize. The same thing can be observed for the set of best individuals from each generation. The trend of the graph in both of the cases shows the same inclination and effect but with a difference in fitness. In fig.5 most of the average individuals stabilize at fitness value o ...
... max point and then stabilize. The same thing can be observed for the set of best individuals from each generation. The trend of the graph in both of the cases shows the same inclination and effect but with a difference in fitness. In fig.5 most of the average individuals stabilize at fitness value o ...
Determination, Uniformity, and Relevance: Normative
... some rules Cor calculating current value, to conclude that the value of Bob's car is about $3500-Cor then it would be unnecessary to invoke the information that Sue's CM is worth that amount. The role of the source analogue (or instance) would in that case be just to point to a conclusion which coul ...
... some rules Cor calculating current value, to conclude that the value of Bob's car is about $3500-Cor then it would be unnecessary to invoke the information that Sue's CM is worth that amount. The role of the source analogue (or instance) would in that case be just to point to a conclusion which coul ...
Efficient Inference in Large Discrete Domains
... those words we have never encountered before). As an other example, consider the problem of person identifica tion [Gill, 1997; Bell and Sethi, 2001], which is the prob lem of comparing a test person's description with each per son's description in the database. When comparing two records, we ha ...
... those words we have never encountered before). As an other example, consider the problem of person identifica tion [Gill, 1997; Bell and Sethi, 2001], which is the prob lem of comparing a test person's description with each per son's description in the database. When comparing two records, we ha ...
Adaptive neural coding: from biological to behavioral decision
... modulation by factors present in the choice set at the time of decision (which we term spatial context, drawing an analogy between the choice set in decision studies and visual space in sensory studies). Under spatial contextdependence, the relative preference between two given alternatives changes ...
... modulation by factors present in the choice set at the time of decision (which we term spatial context, drawing an analogy between the choice set in decision studies and visual space in sensory studies). Under spatial contextdependence, the relative preference between two given alternatives changes ...
Lecture notes for week 5
... “Least-constraining-value” heuristic – once a variable is chosen, choose its value as the one that rules out the fewest choices for neighboring variables. Keeps maximum flexibility for future variable assignments. ...
... “Least-constraining-value” heuristic – once a variable is chosen, choose its value as the one that rules out the fewest choices for neighboring variables. Keeps maximum flexibility for future variable assignments. ...
Evaluation Functions
... Heuristic Evaluating Techniques Evaluation Functions It is not always suitable to search all the possible nodes of a search tree, in order to find a way to the terminal state, as there are things like the time limit. Therefore heuristic evaluations functions, help to determine the state of the game ...
... Heuristic Evaluating Techniques Evaluation Functions It is not always suitable to search all the possible nodes of a search tree, in order to find a way to the terminal state, as there are things like the time limit. Therefore heuristic evaluations functions, help to determine the state of the game ...
A Fast Arc Consistency Algorithm for n-ary Constraints Olivier Lhomme Jean-Charles R´egin
... than any other tuple. The goal of function SEEK VALID S UPPORT is to find a valid support as quickly as possible. For instance, the instantiation of this function for GAC-Scheme+allowed traverses the elements of T (C) until a valid one is found. We propose to accelerate this traversal by exploiting ...
... than any other tuple. The goal of function SEEK VALID S UPPORT is to find a valid support as quickly as possible. For instance, the instantiation of this function for GAC-Scheme+allowed traverses the elements of T (C) until a valid one is found. We propose to accelerate this traversal by exploiting ...