曖昧さ（ambiguity）の下での意思決定について

2016年度第2回研究集会[2016年10月27日(木)]報告要

Regret in Dynamic Decision Problems

The paper proposes a framework to extend regret theory to dynamic contexts. The key idea is to conceive of a dynamic decision problem with regret as an intra-personal game in which the agent forms conjectures about the behaviour of the various counterfactual selves that he could have been. We derive behavioural implications in situations in which payoffs are correlated across either time or contingencies. In the first case, regret might lead to excess conservatism or a tendency to make up for missed opportunities. In the second case, behaviour is shaped by the agent’s self-conception. We relate our results to empirical evidence

Decision Problems For Convex Languages

In this paper we examine decision problems associated with various classes of convex languages, studied by Ang and Brzozowski (under the name "continuous languages"). We show that we can decide whether a given language L is prefix-, suffix-, factor-, or subword-convex in polynomial time if L is represented by a DFA, but that the problem is PSPACE-hard if L is represented by an NFA. In the case that a regular language is not convex, we prove tight upper bounds on the length of the shortest words demonstrating this fact, in terms of the number of states of an accepting DFA. Similar results are proved for some subclasses of convex languages: the prefix-, suffix-, factor-, and subword-closed languages, and the prefix-, suffix-, factor-, and subword-free languages.Comment: preliminary version. This version corrected one typo in Section 2.1.1, line

Decision Problems For Turing Machines

We answer two questions posed by Castro and Cucker, giving the exact complexities of two decision problems about cardinalities of omega-languages of Turing machines. Firstly, it is $D_2(\Sigma_1^1)$-complete to determine whether the omega-language of a given Turing machine is countably infinite, where $D_2(\Sigma_1^1)$ is the class of 2-differences of $\Sigma_1^1$-sets. Secondly, it is $\Sigma_1^1$-complete to determine whether the omega-language of a given Turing machine is uncountable.Comment: To appear in Information Processing Letter

Decision problems for Clark-congruential languages

A common question when studying a class of context-free grammars is whether equivalence is decidable within this class. We answer this question positively for the class of Clark-congruential grammars, which are of interest to grammatical inference. We also consider the problem of checking whether a given CFG is Clark-congruential, and show that it is decidable given that the CFG is a DCFG.Comment: Version 2 incorporates revisions prompted by the comments of anonymous referees at ICGI and LearnAu

Uniform decision problems in automatic semigroups

We consider various decision problems for automatic semigroups, which involve the provision of an automatic structure as part of the problem instance. With mild restrictions on the automatic structure, which seem to be necessary to make the problem well-defined, the uniform word problem for semigroups described by automatic structures is decidable. Under the same conditions, we show that one can also decide whether the semigroup is completely simple or completely zero-simple; in the case that it is, one can compute a Rees matrix representation for the semigroup, in the form of a Rees matrix together with an automatic structure for its maximal subgroup. On the other hand, we show that it is undecidable in general whether a given element of a given automatic monoid has a right inverse.Comment: 19 page

Hardness and inapproximability results for minimum verification set and minimum path decision tree problems

Minimization of decision trees is a well studied problem. In this work, we introduce two new problems related to minimization of decision trees. The problems are called minimum verification set (MinVS) and minimum path decision tree (MinPathDT) problems. Decision tree problems ask the question "What is the unknown given object?". MinVS problem on the other hand asks the question "Is the unknown object z?", for a given object z. Hence it is not an identification, but rather a verification problem. MinPathDT problem aims to construct a decision tree where only the cost of the root-to-leaf path corresponding to a given object is minimized, whereas decision tree problems in general try to minimize the overall cost of decision trees considering all the objects. Therefore, MinVS and MinPathDT are seemingly easier problems. However, in this work we prove that MinVS and MinPathDT problems are both NP-complete and cannot be approximated within a factor in o(lg n) unless P = NP