M.M. De Weerdt

A resource based framework for planning and replanning

We discuss a rigorous unifying framework for both planning and replanning, extending an existing logic-based approach to resource-based planning. The primitive concepts in this action resource framework (ARF) are actions and resources. Actions consume and produce resources. Plans are structures composed of actions, resource facts and an explicit dependency function specifying their interrelationships. In this framework, both planning and replanning are conceived as plan transformation processes accomplished by applying sequences of operations on plans. For this, we introduce operators for plan transformation and define the concept of a plan library. Using a refinement planning template, we show how some existing (re)planning methods and heuristics can be described as special cases of this framework. The advantage of the framework is that it offers a unifying view on planning and replanning.

Dealing with Uncertainty in Operational Transport Planning

An important problem in transportation is how to ensure efficient operational route planning when several vehicles share a common road infrastructure with limited capacity. Examples of such a problem are route planning for automated guided vehicles in a terminal and route planning for aircraft taxiing at airports. Maintaining efficiency in such transport planning scenarios can be difficult for at least two reasons. Firstly, when the infrastructure utilization approaches saturation, traffic jams and deadlocks may occur. Secondly, incidents where vehicles break down may seriously reduce the capacity of the infrastructure and thereby affect the efficiency of transportation. In this chapter we describe a new approach to deal with congestion as well as incidents using an intelligent infrastructure. In this approach, infrastructural resources (road sections, crossings) are capable of maintaining reservations of the use of that resource. Based on this infrastructure, we present an efficient, context-aware, operational transportation planning approach. Experimental results show that our context-aware planning approach outperforms a traditional planning technique and provides robustness in the face of incidents, at a level that allows application to real-world transportation problems.

Mechanism Design for the Online Allocation of Items without Monetary Payments

We consider online mechanism design without money, where agents are allowed to trade items with other agents, in an attempt to improve their own allocation. In an off-line context, this problem is known as the House Allocation Problem (HAP). We extend HAP to an online problem and call it the Online House Allocation Problem (OHAP). In OHAP, agents can choose when to arrive and depart over time and are allowed to be indifferent between items. Subsequently, we present our Agent Shifting Algorithm (ASA) for OHAP. A mechanism that uses ASA as its allocation rule is shown to be strategy-proof, individually rational and Pareto optimal. Moreover, we argue that any mechanism that obtains an outcome in OHAP that cannot be obtained by using ASA fails to be strategy-proof or is not Pareto optimal.