Berge's conjecture on directed path partitions—a survey

AbstractBerge's conjecture from 1982 on path partitions in directed graphs generalizes and extends Dilworth's theorem and the Greene–Kleitman theorem which are well known for partially ordered sets. The conjecture relates path partitions to a collection of k independent sets, for each k⩾1. The conjecture is still open and intriguing for all k>1.11Only recently it was proved Berger and Ben-Arroyo Hartman [56] for k=2 (added in proof). In this paper, we will survey partial results on the conjecture, look into different proof techniques for these results, and relate the conjecture to other theorems, conjectures and open problems of Berge and other mathematicians

An Extension of the Greene and Greene-Kleitman Theorems to all Digraphs

Let G be a directed graph, and k a positive integer. We prove that there exists a k- colouring that is orthogonal to every k-optimal partition of V(G) into paths and cycles. This extends the Greene-Kleitman Theorem to all digraphs, and relates to Berge's conjecture on path partitions and k-colourings. We also show that there exists a colouring that is orthogonal to every optimal collection of k disjoint paths and an arbitrary number of cycles, thus extending Greene's Theorem to all digraphs. We conclude with some conjectures. 1

A New Proof of Berge's Strong Path Partition Conjecture for Acyclic Digraphs

Berge's elegant strong path partition conjecture from 1982 extends the Greene-Kleitman Theorem and Dilworth's Theorem for all digraphs. The conjecture is known to be true for all digraphs for k = 1 by the Gallai-Milgram Theorem, and for k > 1 only for acyclic digraphs. We present a simple algorithmic proof for k = 1 which naturally extends to a new algorithmic proof for acyclic digraphs for all k 1. We conclude with some ideas for extending the algorithm for all digraphs. 1

Berge's Conjecture on Directed Path Partitions -- A Survey

Berge's conjecture from 1982 on path partitions in directed graphs generalizes and extends Dilworth's Theorem and the Greene-Kleitman Theorem which are well known for partially ordered sets. The conjecture relates path partitions to a collection of k independent sets, for each k ≥ 1. The conjecture is still open and intriguing for all k > 1. In this paper, we will survey partial results on the conjecture, look into different proof techniques for these results, and relate the conjecture to other theorems, conjectures and open problems of Berge and other mathematicians

A unified approach to known and unknown cases of Berge's conjecture

Berge's elegant dipath partition conjecture from 1982 states that in a dipath partition P of the vertex set of a digraph minimizing , there exists a collection Ck of k disjoint independent sets, where each dipath P?P meets exactly min{|P|, k} of the independent sets in C. This conjecture extends Linial's conjecture, the GreeneKleitman Theorem and Dilworth's Theorem for all digraphs. The conjecture is known to be true for acyclic digraphs. For general digraphs, it is known for k=1 by the GallaiMilgram Theorem, for k?? (where ?is the number of vertices in the longest dipath in the graph), by the GallaiRoy Theorem, and when the optimal path partition P contains only dipaths P with |P|?k. Recently, it was proved (Eur J Combin (2007)) for k=2. There was no proof that covers all the known cases of Berge's conjecture. In this article, we give an algorithmic proof of a stronger version of the conjecture for acyclic digraphs, using network flows, which covers all the known cases, except the case k=2, and the new, unknown case, of k=?-1 for all digraphs. So far, there has been no proof that unified all these cases. This proof gives hope for finding a proof for all k

Group planning with time constraints

Embedding planning systems in real-world domains has led to the necessity of Distributed Continual Planning (DCP) systems where planning activities are distributed across multiple agents and plan generation may occur concurrently with plan execution. A key challenge in DCP systems is how to coordinate activities for a group of planning agents. This problem is compounded when these agents are situated in a real-world dynamic domain where the agents often encounter differing, incomplete, and possibly inconsistent views of their environment. To date, DCP systems have only focused on cases where agents’ behavior is designed to optimize a global plan. In contrast, this paper presents a temporal reasoning mechanism for self-interested planning agents. To do so, we model agents’ behavior based on the Belief-Desire-Intention (BDI) theoretical model of cooperation, while modeling dynamic join