Symbolic Search in Planning and General Game Playing

Search is an important topic in many areas of AI. Search problems often result in an immense number of states. This work addresses this by using a special datastructure, BDDs, which can represent large sets of states efficiently, often saving space compared to explicit representations. The first part is concerned with an analysis of the complexity of BDDs for some search problems, resulting in lower or upper bounds on BDD sizes for these. The second part is concerned with action planning, an area where the programmer does not know in advance what the search problem will look like. This part presents symbolic algorithms for finding optimal solutions for two different settings, classical and net-benefit planning, as well as several improvements to these algorithms. The resulting planner was able to win the International Planning Competition IPC 2008. The third part is concerned with general game playing, which is similar to planning in that the programmer does not know in advance what game will be played. This work proposes algorithms for instantiating the input and solving games symbolically. For playing, a hybrid player based on UCT and the solver is presented

Artificial intelligence techniques for assembly process planning

Due to current trends in adopting flexible manufacturing philosophies, there has been a growing interest in applying Artificial Intelligence (AI) techniques to implement these manufacturing strategies. This is because conventional computational methods alone are not sufficient to meet these requirements for more flexibility. This research examines the possibility of applying AI techniques to process planning and also addresses the various problems when implementing such techniques. In this project AI planning techniques were reviewed and some of these techniques were adopted and later extended to develop an assembly planner to illustrate the feasibility of applying AI techniques to process planning. The focus was on assembly process planning because little work in this area has been reported. Logical decisions like the sequencing of tasks which is a part of the process planning function can be viewed as an AI planning problem. The prototype Automatic Assembly Planner (AAP) was implemented using Edinburgh Prolog on a SUN workstation. Even though expected assembly sequences were obtained, the major problem facing this approach and perhaps AI applications in general is that of extracting relevant design data for the process planning function as illustrated by the planner. It is also believed that if process planning can be regarded as making logical decisions with the knowledge of company specific data then perhaps AAP has also provided some possible answers as to how human process planners perform their tasks. The same kind of reasoning for deciding the sequence of operations could also be employed for planning different products based on a different set of company data. AAP has illustrated the potentialities of applying AI techniques to process planning. The complexity of assembly can be tackled by breaking assemblies into sub-goals. The Modal Truth Criterion (MTC) was applied and tested in a real situation. A system for representing the logic of assembly was devised. A redundant goals elimination feature was also added in addition to the MTC in the AAP. Even though the ideal is a generative planner, in practice variant planners are still valid and perhaps closer to manual assembly process planning

First Annual Workshop on Space Operations Automation and Robotics (SOAR 87)

Several topics relative to automation and robotics technology are discussed. Automation of checkout, ground support, and logistics; automated software development; man-machine interfaces; neural networks; systems engineering and distributed/parallel processing architectures; and artificial intelligence/expert systems are among the topics covered

Tools and Algorithms for the Construction and Analysis of Systems

This open access two-volume set constitutes the proceedings of the 26th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The total of 60 regular papers presented in these volumes was carefully reviewed and selected from 155 submissions. The papers are organized in topical sections as follows: Part I: Program verification; SAT and SMT; Timed and Dynamical Systems; Verifying Concurrent Systems; Probabilistic Systems; Model Checking and Reachability; and Timed and Probabilistic Systems. Part II: Bisimulation; Verification and Efficiency; Logic and Proof; Tools and Case Studies; Games and Automata; and SV-COMP 2020

NBS monograph

From Introduction: "This is the third in a planned series of reports involving selective literature reviews of research and development requirements and areas of continuing R & D concern in the computer and information sciences and technologies.