Reactive Plans Research Articles

Reactivity and statefulness: Action-based sensors, plans, and necessary state

Typically to a roboticist, a plan is the outcome of other work, a synthesized object that realizes ends defined by some problem; plans qua plans are seldom treated as first-class objects of study. Plans designate functionality: a plan can be viewed as defining a robot’s behavior throughout its execution. This informs and reveals many other aspects of the robot’s design, including: necessary sensors and action choices, history, state, task structure, and how to define progress. Interrogating sets of plans helps in comprehending the ways in which differing executions influence the interrelationships between these various aspects. Revisiting Erdmann’s theory of action-based sensors, a classical approach for characterizing fundamental information requirements, we show how plans (in their role of designating behavior) influence sensing requirements. Using an algorithm for enumerating plans, we examine how some plans for which no action-based sensor exists can be transformed into sets of sensors through the identification and handling of features that preclude the existence of action-based sensors. We are not aware of those obstructing features having been previously identified. Action-based sensors may be treated as standalone reactive plans; we relate them to the set of all possible plans through a lattice structure. This lattice reveals a boundary between plans with action-based sensors and those without. Some plans, specifically those that are not reactive plans and require some notion of internal state, can never have associated action-based sensors. Even so, action-based sensors can serve as a framework to explore and interpret how such plans make use of state.

Over Pressure Risk Mitigation with SCADA in a Natural Gas Distribution System

Natural gas distribution providers have periodic and reactive maintenance plans that are not providing enough feedback and data to establish proper predictive analysis for failure, especially on distribution gas regulator station that are regulating gas from transmission pressure to a safe customer distribution pressure, these stations are the only overpressure safeguard and the highest risk at the same time. With the recent advances in computer and telecommunications technologies, some major gas utilities initiated more robust predictive risk analysis plans by introducing SCADA supervisory control and data acquisition to gas distribution, mainly monitoring gas regulator stations and their behavior based on their established overpressure prevention philosophies and long-term predictive analysis goals. This study outlines a full SCADA monitoring solution on a dual run gas distribution regulator station equipped with primary overpressure protection and redundancy options. RTU (Remote Terminal Units) containing flow and pressure monitoring transmitters are installed at specific pressure reduction points in the station piping. Unlike common monitoring practice, we are introducing mid-stream pressure monitoring between the monitor and regular valves, filter differential and flow measurement in our proposed SCADA set up. This system provides real time visibility and data to the gas control room to quickly recognize abnormal or emergency events and assess the current health of regulator equipment. The outlined risk mitigations in this study are created based on identified risks of overpressure under several regulation failure modes of the regulators in standby and working modes. Our SCADA solution introduces means to enhance deductive analysis and predictability for gas control departments and monitoring groups leading to a safer and more reliable gas distribution system, improving emergency response and creating more comprehensive maintenance plans driven by long term predictive risk plans.

Shared representations of actions for alternative suggestion with incomplete information

Common coding theory posits there are cycles between perceptions and actions at the fundamental logic of the nervous system. An action performed by an agent modifies its external environment and/or internal states. The agent is able to complete a given goal by performing a sequence of actions. In this work, shared representations for both perception and action and their processing algorithm are presented that suggest goal-oriented alternative actions even with incomplete information. The alternative actions provide more opportunities for a service robot to achieve goals. Knowledge plays significant roles to successfully complete service tasks. Most knowledge inference mechanisms assume complete and correct knowledge about the environment. Real world environments are often uncertain and only partially observable. Thus, intelligent service robots may have an incomplete knowledge base which includes false negatives and false positives as well as true positives. False negatives and false positives can prevent service robots from completing their service tasks. A case study reveals that the proposed method has proved valuable to suggest alternatives for false information as well as to build reactive plans with customary efficiency.

A NOVEL APPROACH FOR SOLVING THE DYNAMIC VEHICLE ROUTING PROBLEM BASED ON HIERARCHICAL SELF-ORGANIZING MAPS

Dynamic routing problems ask for policies and algorithms to build reactive plans able to integrate dynamically generated requests in currently running plans. The main desired quality of such approaches is to overcome the lack of information availability in the beginning of the solving process. That is by proposing flexible partial solutions anticipating future requests. In this paper, we propose a neural model based on Hierarchical self-organizing maps (HSOM) for solving the dynamic vehicle routing problem (DVRP). The DVRP consists of finding routes for a set of vehicles to serve customer's dynamically issued requests while minimizing routing costs and satisfying some constraints. We present the concept of problem control bloc (PCB) to represent the problem to solve by the HSOM algorithm when triggered by a new event. The overall solving approach is integrated within a discrete event manager that will wait for any new event to build the PCB, call the HSOM solver, get the proposed solution and update the running plan accordingly. The proposed approach was applied to solve the DVRP problems adapted from VRP benchmarks. The obtained results are compared to the best known solutions.

A loop acceleration technique to speed up verification of automatically generated plans

The CIRCA planning system automatically creates reactive plans and uses formal verification techniques to prove that those plans will preserve system safety. CIRCA's timed automata verification system is highly efficient, yet can display pathologically bad behavior when reasoning about reaction loops, a particular form of interacting cycles of states. In this paper, we describe a loop acceleration technique that recognizes these state-space structures during the verification process and bypasses the process of expanding an arbitrarily large cycle of states, effectively compressing loops of arbitrary size into a compact, finite set of states. The resulting performance improvement can be very dramatic: in domains where tight loops of short-duration transitions interact with long-duration transitions, our new loop acceleration methods can reduce verification time (and hence planning time) from hours to below a second.

Climate Change and Hydropower Planning in the Middle East: Implications for Iran’s Karkheh Hydropower Systems

AbstractGiven the important role of hydropower in peak electricity management, Middle Eastern countries are actively pursuing development of more hydropower resources by construction of large dams. Nonetheless, climate change is expected to affect the future productivity of hydropower by influencing the hydrologic cycle and different climate variables in the region. Although reactive plans to minimize climate change impacts on hydropower production have been implemented in the developed world, the developing world can still benefit from proactive actions. Studies of climate change impacts before and during implementation of hydropower projects can result in timely responses and adaptation to climate change with a potential of considerable cost savings. This study investigates the potential impacts of climate change on the hydropower systems in the Karkheh River Basin—the third largest river basin in Iran—in terms of potential for hydroelectricity generation. A simulation model is developed to examine how ...

The Influence of Mental Skills on Motivation and Psychosocial Characteristics

The purpose of this observational, cross-sectional study was to assess psychosocial characteristics and intrinsic motivation in a convenience sample of Army soldiers with different mental skills profiles. Participants were recruited immediately before or immediately following regular training activities. Anonymous surveys were completed and collected in the training area. Instruments used in this study included the Ottawa Mental Skills Assessment Tool-3 Revised for Soldiers; Rosenberg Self-esteem Scale; Depression Anxiety Stress Scale-21; University of California, Los Angeles, Loneliness Scale; Beck Hopelessness Scale; Intrinsic Motivation Inventory; and an anger measure. Soldiers with strong mental skill profiles were more intrinsically motivated and psychosocially healthier than their peers with weaker mental skill profiles. It is recommended that a proactive approach to psychological health promotion practices in soldiers be sought rather than reactive treatment plans to psychological sequelae. Future research must examine the role of psychosocial fitness and adaptability to enhance mental skills fitness.

The Management and Treatment of Challenging Behaviours

The paper considers the kinds of treatment available for people with learning disabilities and challenging behaviour. It draws on research data on the use of reactive strategies and behaviour plans for 235 children and adults rated by carers as extremely challenging, and 276 rated as very challenging, to identify any trends in the management and treatment of challenging behaviour. It finds an increase in written plans for adults but not for children, and no information on the extent to which plans are based on sound functional analyses and contain proactive as well as reactive strategies. Only half the plans were said to have been drawn up with any support from behavioural specialists, and there was no discernible change in the use of reactive strategies.

Toward behavioral intelligence in the Semantic Web

Realizing the Web's full potential will require the development and support of agents that function as schedulers, planners, and searchers who, with minimal direction, can serve as an omnipresent staff of advisers, secretaries, brokers, and research assistants. Electronic commerce has brought this capability tantalizingly near. Organizations and individuals have connected an enormous variety of products and services to the Internet, making them accessible to other programs through simple communication protocols. Now the AI community must determine how it can build intelligent agents to exploit these services. One strategy would change the Web itself, making it accessible to existing AI modeling, and reasoning techniques. In this semantic Web, service and content providers would mark pages in accordance with standardized conventions designed to reduce ambiguity and make automated reasoning easier. The paper considers the development of a distributed intelligence and bringing agents to the Web. It discusses DAML-S which provides support for composite services, combinations of simpler services, or behaviors, and the coordination mechanisms, or reactive plans, used to combine those behaviors.

Learning Plans without a priori Knowledge

This paper is concerned with the autonomous learning of plans in probabilistic domains with out a priori domain-specific knowledge. In contrast to existing reinforcement learning algorithms that generate only reactive plans, and existing probabilistic planning algorithms that require a sub stantial amount of a priori knowledge in order to plan, a two-stage bottom-up process is devised in which first reinforcement learning/dynamic programming is applied, without the use of a pri ori domain-specific knowledge, to acquire a reactive plan, and then explicit plans are extracted from the reactive plan. Several options for plan extraction are examined, each of which is based on a beam search that performs temporal projection in a restricted fashion, guided by the value functions resulting from reinforcement learning/dynamic programming. Some completeness and soundness results are given. Examples in several domains are discussed that together demonstrate the working of the proposed model.

Recent research on physical aggression in persons with intellectual disability: An overview

Physically aggressive behaviours pose major problems to carers supporting people with intellectual disability. This review considers the prevalence and nature of this form of challenging behaviour within this population and describes possible causal factors. The present status of both behavioural and pharmacological interventions for aggression are assessed, and the importance of devising reactive management plans for aggressive behaviours outlined. Implications for future practice are discussed.

Integrating active localization into high-level robot control systems

High-level control systems are designed to enable mobile robots to successfully perform complex missions such as office delivery and survillance tasks. For that purpose they have to control, coordinate, and monitor different kinds of subtasks like navigation, manipulation, and perception. An important aspect of the effectiveness of high-level control systems is the ability to cope with failures that occur during the execution of such subtaks. In this paper we focus on the particular subtask of estimating the position of the robot and show how to achieve its robust integration into the high-level control system. The principle of this integration is to monitor the certainty of the position estimation and to autonomously relocalize the robot whenever the uncertainly grows too large. We present a localization approach which accurately and efficiently keeps track of the robot's position. Furthermore, it provides a measure for detecting localization failures and it is able to autonomously relocalize the robot in such situations. In addition to this, we introduce structured reactive plans, which can be interrupted by such active localization processes at any point in time and allow the robot to complete its mission afterwards. Our method has been implemented and shown to be robust in long-term experiments involving a typical office delivery scenario.

Planning control rules for reactive agents

A traditional approach for planning is to evaluate goal statements over state trajectories modeling predicted behaviors of an agent. This paper describes a powerful extension of this approach for handling complex goals for reactive agents. We describe goals by using a modal temporal logic that can express quite complex time, safety, and liveness constraints. Our method is based on an incremental planner algorithm that generates a reactive plan by computing a sequence of partially satisfactory reactive plans converging to a completely satisfactory one. Partial satisfaction means that an agent controlled by the plan accomplishes its goal only for some environment events. Complete satisfaction means that the agent accomplishes its goal whatever environment events occur during the execution of the plan. As such, our planner can be stopped at any time to yield a useful plan. An implemented prototype is used to evaluate our planner on empirical problems.

Ginsberg Replies to Chapman and Schoppers

Rather than begin by discussing the points where I seem to be in disagreement with Chapman and Schoppers, let me start with something about which we seem to concur: The work on reactive plans can be broken into two parts. First is the work on pure reac-tive plans, which specify actions for an agent to take in all situations. Second is the work on caching reactive plans, which specify actions in only some instances and are primarily used to store the results of previous planning activ-ity. Although Chapman would object to the use of the word plan, the basic distinction is one that his reply appears to sanction.