An integral theorem prover and the role of proof planning

An investigation is made into the ways proof planning can enhance the capability of a rule based prover for the theory of integration. The integrals are of the Riemann type and are defined in a way to maximize the theorem proving methods of predicate calculus. Approximately fifty theorems have been proved and several examples are discussed. A major shortcoming was found to be the inability of the system to work with or produce a proof plan. As a result, a planning scheme based on the idea of subgoals or milestones was considered. With user defined plans, there was a substantial increase in performance and capability of the system and, in some cases, proofs which were previously unsuccessful were completed.     

Planning the GMAW process by constraint propagation

Although the gas metal arc welding (GMAW) process is widely used for joining metals, its planning is still a cumbersome task. The planning procedure involves many complex interrelationships among the process variables and depends heavily on empirical knowledge. Therefore, a solution method that allows a convenient way to represent the domain knowledge and evaluate the process variable relationships is needed. Further, the lack of a strong domain theory to quantify these interrelationships is a deficiency in the planning of the GMAW process. This paper presents a solution method that overcomes this deficiency and introduces a convenient knowledge representation scheme. The solution method considers the planning procedure to be a constraint satisfaction problem (CSP). The AC-4 algorithm is used to obtain arc consistency among nodes in the constraint network and the PC-4 algorithm is applied to obtain path consistency in the network. A modified version of the AC-4 algorithm is developed to reduce the search space and correspondingly reduce the computation time. An example is presented to demonstrate the capability of the method and its potential to reduce lead time.     

The Influence of Gravity on Trajectory Planning for Climbing Robots with Non-Rigid Legs

In this paper questions related to the occurrence of departures of a legged climbing robot from the given trajectory are considered. The basic idea of the paper is to show that, if there are slackness and non-rigidities, the legged climbing robot moving upon an inclined or vertical plane, departs systematically from the planned trajectory. It is demonstrated that these departures result from the gravity and are of systematic character. It is also shown how the inclusion of torsion effect changes substantially the nature of systematic errors arising from robot's movement along the inclined surface.     

浅谈前海物流园规划构想

探讨了深圳前海物流园区的地理条件及发展的重要因素，针对其存在的交通设施不足，管理不到位等问题进行了分析，并结合功能定位从用地规模、功能布局等方面提出了规划设计构想。     

探讨低收入阶层住区建设的公共政策

探讨了低收入阶层住区建设的现状及弊端，从旧城改造、新城建设及住房政策三方面对解决低收入阶层住区建设问题的对策进行了研究，以妥善解决低收入阶层的住房问题，从而达到构建和谐社会的目的。     

基于非确定性思考下的城市规划新思维探讨

通过对城市规划编制与实施过程中的问题分析，提出非确定性城市规划思想的理念以及非确定性规划思想与确定性规划思想的差别，并在分析非确定性规划思想内涵的基础上，提出非确定性规划思想指导下的城市规划的新程式。     

Synthesizing plans that contain actions with context-dependent effects1

This paper presents a method of solving planning problems that involve actions whose effects change according to the situations in which they are performed. The approach is an extension of the conventional planning methodology in which plans are constructed through an iterative process of scanning for goals that are not yet satisfied, inserting actions to achieve them, and introducing subgoals to these actions. This methodology was originally developed under the assumption that one would be dealing exclusively with actions that produce the same effects in every situation. The extension involves introducing additional subgoals to actions above and beyond the preconditions of execution normally introduced. These additional subgoals, called secondary preconditions, ensure that the actions are performed in contexts conducive to producing the effects we desire. This paper defines and analyzes secondary preconditions from a mathematically rigorous standpoint and demonstrates how they can be derived from regression operators.     

Casual reasoning in planning1

Reasoning about actions necessarily involves tracking the truth of assertions about the world over time. The SIPE planning system retains the efficiency of the STRIPS assumption for this while enhancing expressive power by allowing the specification of a causl theory. Separation of knowledge about causality from knowledge about actions relieves operators of much of their representational burden and allows them to be applicable in a wide range of contexts. The implementation of causal theories is described, together with examples and evaluations of the system's expressive power and efficiency.     

ERP编码系统的研究与设计

提出了ERP编码的原则，介绍了常见的四种编码方法：顺序码、分类码、结构码和组合码．最后结合实例介绍了编码系统中各模块的设计。     

Application of parallelized analogical planning to engineering design

Analogical planning provides a means of solving engineering problems where other machine learning methods fail. Unlike many machine learning paradigms, analogy does not require numerous previous examples or a rich domain theory. Instead, analogical planners adapt knowledge of solved problems in similar domains to the current problem. Unfortunately, the analogical planning task is an expensive one. While the process of forming correspondences between a known problem and a new problem is complex, the problem of selecting a base case for the analogy is virtually intractable.This paper addresses the issue of efficiently forming analogical plans. The Anagram planning system is described, which takes advantage of the massively parallel architecture of the Connection Machine to perform base selection and map formation. Anagram provides a tractable solution to analogical planning, with a complexity that is sublinear in the size of the plans.This paper describes the Anagram system and its parallel algorithms. The paper also presents theoretical analyses and empirical results of testing the system on a large database of plans from the domain of automatic programming.