scholarly journals A Model of Path-Dependence in Decisions over Multiple Propositions

2004 ◽  
Vol 98 (3) ◽  
pp. 495-513 ◽  
Author(s):  
CHRISTIAN LIST
Keyword(s):  
Decision Making ◽  
Decision Process ◽  
Propositional Logic ◽  
Path Dependence ◽  
Strategic Voting ◽  
Sequential Decision ◽  
Sequential Decisions ◽  
Sequential Decision Process ◽  
Path Dependent ◽  
Necessary And Sufficient

I model sequential decisions over multiple interconnected propositions and investigate path-dependence in such decisions. The propositions and their interconnections are represented in propositional logic. A sequential decision process is path-dependent if its outcome depends on the order in which the propositions are considered. Assuming that earlier decisions constrain later ones, I prove three main results: First, certain rationality violations by the decision-making agent—individual or group—are necessary and sufficient for path-dependence. Second, under some conditions, path-dependence is unavoidable in decisions made by groups. Third, path-dependence makes decisions vulnerable to strategic agenda setting and strategic voting. I also discuss escape routes from path-dependence. My results are relevant to discussions on collective consistency and reason-based decision-making, focusing not only on outcomes, but also on underlying reasons, beliefs, and constraints.

STRONG REPRESENTATION OF A DISCRETE DECISION PROCESS BY POSITIVELY/NEGATIVELY BITONE SEQUENTIAL DECISION PROCESS

2007 ◽  
Vol 24 (02) ◽  
pp. 181-202
Author(s):  
YUKIHIRO MARUYAMA
Keyword(s):  
Representation Theorem ◽  
Decision Process ◽  
Sufficient Condition ◽  
Necessary And Sufficient Condition ◽  
Sequential Decision ◽  
Sequential Decision Process ◽  
Strong Representation ◽  
Necessary And Sufficient

In this paper, we will introduce a new subclass of bitone sequential decision process (bsdp) and give a representation theorem for the subclass called positively/negatively bsdp, shortly, p/n bsdp, that is, necessary and sufficient condition for p/n bsdp to strongly represent a given discrete decision process (ddp).

Deterministic policies based on maximum regrets in MDPs with imprecise rewards

2021 ◽  
pp. 1-16
Author(s):  
Pegah Alizadeh ◽  
Emiliano Traversi ◽  
Aomar Osmani
Keyword(s):  
Decision Making ◽  
Decision Process ◽  
Process Models ◽  
Sequential Decision Making ◽  
Sequential Decision ◽  
Exact Procedure ◽  
Markov Decision ◽  
Intuitive Idea ◽  
First Time ◽  
Maximum Regret

Markov Decision Process Models (MDPs) are a powerful tool for planning tasks and sequential decision-making issues. In this work we deal with MDPs with imprecise rewards, often used when dealing with situations where the data is uncertain. In this context, we provide algorithms for finding the policy that minimizes the maximum regret. To the best of our knowledge, all the regret-based methods proposed in the literature focus on providing an optimal stochastic policy. We introduce for the first time a method to calculate an optimal deterministic policy using optimization approaches. Deterministic policies are easily interpretable for users because for a given state they provide a unique choice. To better motivate the use of an exact procedure for finding a deterministic policy, we show some (theoretical and experimental) cases where the intuitive idea of using a deterministic policy obtained after “determinizing” the optimal stochastic policy leads to a policy far from the exact deterministic policy.

Path Dependence

2017 ◽  
Author(s):  
Michelle Hegmon
Keyword(s):  
Decision Making ◽  
Path Dependence ◽  
General Level ◽  
Historical Contingency ◽  
Difficult Decision ◽  
Critical Junctures ◽  
Potential Applications ◽  
Path Dependent ◽  
Historical Sequences ◽  
Lock In

Path dependence concepts, thus far, have seen little application in archaeology, but they have great potential. At a general level, these concepts provide tools for theorizing historical sequences, such as patterns of settlement on a landscape and divergent historical traditions. Potential applications include issues of historical contingency in the late Rio Grande, settlement in the Mesa Verde region, and divergent trajectories in the post-Chaco period. Specific concepts from path dependence theory, including lock-in and critical junctures, are illustrated by an analysis of the growth of Hohokam irrigation, which exhibited a path-dependent trajectory. As archaeological study of path dependence builds awareness of the importance of decision-making on the future, it contributes to difficult decision-making in today’s world.

Design as a Sequential Decision Process: A Method for Reducing Design Set Space Using Models to Bound Objectives

2015 ◽  
Author(s):  
Simon W. Miller ◽  
Timothy W. Simpson ◽  
Michael A. Yukish
Keyword(s):  
Decision Process ◽  
Search Space ◽  
Decision Makers ◽  
Sequential Decision ◽  
Modeling And Analysis ◽  
One Dimensional ◽  
Selection Policy ◽  
Sequential Decision Process ◽  
Formal Definitions ◽  
Optimal Modeling

Design is a sequential decision process that increases the detail of modeling and analysis while simultaneously decreasing the space of alternatives considered. In a decision theoretic framework, low-fidelity models help decision-makers identify regions of interest in the tradespace and cull others prior to constructing more computationally expensive models of higher fidelity. The method presented herein demonstrates design as a sequence of finite decision epochs through a search space defined by the extent of the set of designs under consideration, and the level of analytic fidelity subjected to each design. Previous work has shown that multi-fidelity modeling can aid in rapid optimization of the design space when high-fidelity models are coupled with low-fidelity models. This paper offers two contributions to the design community: (1) a model of design as a sequential decision process of refinement using progressively more accurate and expensive models, and (2) a connected approach for how conceptual models couple with detailed models. Formal definitions of the process are provided, and a simple one-dimensional example is presented to demonstrate the use of sequential multi-fidelity modeling in determining an optimal modeling selection policy.

Structural Design Synthesis Through a Sequential Decision Process

2020 ◽  
Author(s):  
Maximilian E. Ororbia ◽  
Gordon P. Warn
Keyword(s):  
Structural Design ◽  
Decision Process ◽  
Truss Structures ◽  
Design Solution ◽  
Sequential Decision ◽  
Structural Configuration ◽  
Design Synthesis ◽  
Numerical Examples ◽  
Sequential Decision Process ◽  
Markov Decision

Abstract This article illustrates that structural design synthesis can be achieved through a sequential decision process, whereby a sparsely connected seed configuration is sequentially altered through discrete actions to generate the best design solution, with respect to a specified objective and constraints. Specifically, the generative design synthesis is mathematically formulated as a finite Markov Decision Process. In this context, the states correspond to a specific structural configuration, the actions correspond to the available alterations that can be made to a given configuration, and the immediate rewards are constructed to be proportional to the improvement in the altered configuration’s performance. In the context of generative structural design synthesis, since the immediate rewards are not known at the onset of the process, reinforcement learning is employed to obtain an approximately optimal policy by which to alter the seed configuration to synthesize the best design solution. The approach is applied for the optimization of planar truss structures and its utility is investigated with three numerical examples, each with unique domains and constraints.

Increasing the discriminatory power of bounding models using problem-specific knowledge when viewing design as a sequential decision process

2020 ◽  
Vol 62 (2) ◽  
pp. 709-728
Author(s):  
Maximilian E. Ororbia ◽  
Jaskanwal P. S. Chhabra ◽  
Gordon P. Warn ◽  
Simon W. Miller ◽  
Michael A. Yukish ◽  
...  
Keyword(s):  
Decision Process ◽  
Discriminatory Power ◽  
Sequential Decision ◽  
Specific Knowledge ◽  
Sequential Decision Process
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