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This article studies the problem of modifying the action ordering of a plan in order to optimise the plan according to various criteria. One of these criteria is to make a plan less constrained and the other is to minimize its parallel…

Artificial Intelligence · Computer Science 2011-05-30 C. Backstrom

We present a heuristic algorithm for solving the problem of scheduling plans of tasks. The plans are ordered vectors of tasks, and tasks are basic operations carried out by resources. Plans are tied by temporal, precedence and resource…

Artificial Intelligence · Computer Science 2021-02-09 Davide Andrea Guastella

Qualitative numerical planning is classical planning extended with non-negative real variables that can be increased or decreased "qualitatively", i.e., by positive indeterminate amounts. While deterministic planning with numerical…

Artificial Intelligence · Computer Science 2020-11-30 Blai Bonet , Hector Geffner

We explore a multiple-stage variant of the min-max robust selection problem with budgeted uncertainty that includes queries. First, one queries a subset of items and gets the exact values of their uncertain parameters. Given this…

Optimization and Control · Mathematics 2025-01-07 Xiaoyu Chen , Marc Goerigk , Michael Poss

We formalize the problem of selecting the optimal set of options for planning as that of computing the smallest set of options so that planning converges in less than a given maximum of value-iteration passes. We first show that the problem…

Artificial Intelligence · Computer Science 2019-03-19 Yuu Jinnai , David Abel , D Ellis Hershkowitz , Michael Littman , George Konidaris

Numeric planning with control parameters extends the standard numeric planning model by introducing action parameters as free numeric variables that must be instantiated during planning. This results in a potentially infinite number of…

Artificial Intelligence · Computer Science 2025-12-30 Ángel Aso-Mollar , Diego Aineto , Enrico Scala , Eva Onaindia

This survey is focused on certain sequential decision-making problems that involve optimizing over probability functions. We discuss the relevance of these problems for learning and control. The survey is organized around a framework that…

Optimization and Control · Mathematics 2023-01-13 Emiland Garrabe , Giovanni Russo

Many academic disciplines - including information systems, computer science, and operations management - face scheduling problems as important decision making tasks. Since many scheduling problems are NP-hard in the strong sense, there is a…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-05-26 Gerhard Rauchecker , Guido Schryen

Dealing with planning problems with both logical relations and numeric changes in real-world dynamic environments is challenging. Existing numeric planning systems for the problem often discretize numeric variables or impose convex…

Artificial Intelligence · Computer Science 2022-10-11 Kebing Jin , Hankz Hankui Zhuo , Zhanhao Xiao , Hai Wan , Subbarao Kambhampati

Temporal planning often involves numeric effects that are directly proportional to their action's duration. These include continuous effects, where a numeric variable is subjected to a rate of change while the action is being executed, and…

Artificial Intelligence · Computer Science 2022-02-01 Josef Bajada , Maria Fox , Derek Long

The ability to generate multiple plans is central to using planning in real-life applications. Top-quality planners generate sets of such top-cost plans, allowing flexibility in determining equivalent ones. In terms of the order between…

Artificial Intelligence · Computer Science 2024-04-03 Michael Katz , Junkyu Lee , Jungkoo Kang , Shirin Sohrabi

For many years, the intuitions underlying partial-order planning were largely taken for granted. Only in the past few years has there been renewed interest in the fundamental principles underlying this paradigm. In this paper, we present a…

Artificial Intelligence · Computer Science 2009-09-25 S. Minton , J. Bresina , M. Drummond

This paper describes a novel approach to planning which takes advantage of decision theory to greatly improve robustness in an uncertain environment. We present an algorithm which computes conditional plans of maximum expected utility. This…

Artificial Intelligence · Computer Science 2013-02-28 Stephen G. Pimentel , Lawrence M. Brem

We represent planning as a set of loosely coupled network flow problems, where each network corresponds to one of the state variables in the planning domain. The network nodes correspond to the state variable values and the network arcs…

Artificial Intelligence · Computer Science 2011-11-02 Menkes Hector Louis van den Briel , Thomas Vossen , Subbarao Kambhampati

We study a natural variant of scheduling that we call \emph{partial scheduling}: In this variant an instance of a scheduling problem along with an integer $k$ is given and one seeks an optimal schedule where not all, but only $k$ jobs, have…

Data Structures and Algorithms · Computer Science 2020-10-02 Jesper Nederlof , Céline Swennenhuis

Classical planning asks for a sequence of operators reaching a given goal. While the most common case is to compute a plan, many scenarios require more than that. However, quantitative reasoning on the plan space remains mostly unexplored.…

Artificial Intelligence · Computer Science 2025-02-04 David Speck , Markus Hecher , Daniel Gnad , Johannes K. Fichte , Augusto B. Corrêa

We examine the computational complexity of testing and finding small plans in probabilistic planning domains with both flat and propositional representations. The complexity of plan evaluation and existence varies with the plan type sought;…

Artificial Intelligence · Computer Science 2007-05-23 M. L. Littman , J. Goldsmith , M. Mundhenk

Decisions are often based on imprecise, uncertain or vague information. Likewise, the consequences of an action are often equally unpredictable, thus putting the decision maker into a twofold jeopardy. Assuming that the effects of an action…

General Economics · Economics 2022-05-03 Stefan Rass , Sandra König , Stefan Schauer

Multi-mode resource and precedence-constrained project scheduling is a well-known challenging real-world optimisation problem. An important variant of the problem requires scheduling of activities for multiple projects considering…

Data Structures and Algorithms · Computer Science 2016-09-09 Shahriar Asta , Daniel Karapetyan , Ahmed Kheiri , Ender Özcan , Andrew J. Parkes

Recognition of goals and plans using incomplete evidence from action execution can be done efficiently by using planning techniques. In many applications it is important to recognize goals and plans not only accurately, but also quickly. In…

Artificial Intelligence · Computer Science 2017-02-08 Ramon Fraga Pereira , Felipe Meneguzzi
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