Design Concepts for a new Temporal Planning Paradigm

Abstract Throughout the history of space exploration, the complexity of missions has dramatically increased, from Sputnik in 1957 to MSL, a Mars rover mission launched in November 2011 with advanced autonomous capabilities. As a result, the mission plan that governs a spacecraft has also grown in complexity, pushing to the limit the capability of human operators to understand and manage it. However, the effective representation of large plans with multiple goals and constraints still represents a problem. In this paper, a novel approach to address this problem is presented. We propose a new planning paradigm named HTLN, intended to provide a compact and understandable representation of complex plans and goals based on Timeline planning and Hierarchical Temporal Networks. We also present the design of a planner based on HTLN, which enables new planning approaches that can improve the performance of present real-world domains

Multiple hypernode hitting sets and smallest two-cores with targets

The multiple weighted hitting set problem is to find a subset of nodes in a hypergraph that hits every hyperedge in at least m nodes. We extend the problem to a notion of hypergraphs with so-called hypernodes and show that it remains fixed-parameter tractable (FPT) for m=2, with the number of hyperedges as the parameter. This is accomplished by a nontrivial extension of the known dynamic programming algorithm for usual hypergraphs. The result might be of independent interest for assignment problems, but here we need it as an auxiliary result to solve a different problem motivated by network analysis: We give an FPT algorithm that computes a smallest 2-core including a given set of target vertices in a graph, with the number of targets as the parameter. (A d-core is a subgraph where every vertex has degree at least d within the subgraph.) This FPT result is best possible, in the sense that an FPT algorithm for 3-cores cannot exist, for simple reasons

Multiple hypernode hitting sets and smallest two-cores with targets

The multiple weighted hitting set problem is to find a subset of nodes in a hypergraph that hits every hyperedge in at least m nodes. We extend the problem to a notion of hypergraphs with so-called hypernodes and show that, for m=2, it remains fixed-parameter tractable (FPT), parameterized by the number of hyperedges. This is accomplished by a nontrivial extension of the dynamic programming algorithm for hypergraphs. The algorithm might be interesting for certain assignment problems, but here we need it as a tool to solve another problem motivated by network analysis: A d-core of a graph is a subgraph in which every vertex has at least d neighbors. We give an FPT algorithm that computes a smallest 2-core including a given set of target vertices, where the number of targets is the parameter. This FPT result is best possible in the sense that no FPT algorithm for 3-cores can be expected

Multiple hypernode hitting sets and smallest two-cores with targets

The multiple weighted hitting set problem is to find a subset of nodes in a hypergraph that hits every hyperedge in at least m nodes. We extend the problem to a notion of hypergraphs with so-called hypernodes and show that it remains fixed-parameter tractable (FPT) for m=2, with the number of hyperedges as the parameter. This is accomplished by a nontrivial extension of the known dynamic programming algorithm for usual hypergraphs. The result might be of independent interest for assignment problems, but here we need it as an auxiliary result to solve a different problem motivated by network analysis: We give an FPT algorithm that computes a smallest 2-core including a given set of target vertices in a graph, with the number of targets as the parameter. (A d-core is a subgraph where every vertex has degree at least d within the subgraph.) This FPT result is best possible, in the sense that an FPT algorithm for 3-cores cannot exist, for simple reasons