Pub Date : 1992-07-08DOI: 10.1109/AIHAS.1992.636897
Li Dafa
Let L1 v C1 and L2 V Cz be two parent clauses, where L1 and Lz are positive literals, C1 and C2 are clauses. If L1 and Lz have a most general unifier U and there is the most general substitution X such that ClaX 5 C ~ U A , then CzaX is called an inclusive resolvent of L1 v Cl and L2 v C2. The problem is whether the inclusive resolution is complete. The lifting lemma for inclusive resolution is proved, then it is proved that the inclusive resolution is complete for Horn sets. The present paper gives the inclusion algorithm, and the inclusion theorem is proved.
设L1 v C1和L2 v Cz为两个父子句，其中L1和Lz是正数，C1和C2是子句。如果L1和Lz有一个最一般的统一子U并且有一个最一般的替换X使得ClaX 5c ~ ua，那么CzaX就被称为l1v Cl和l2v C2的包容解。问题在于包容性解决方案是否完整。首先证明了包含分辨的提升引理，然后证明了Horn集合的包含分辨是完全的。本文给出了包含算法，并证明了包含定理。
{"title":"Inclusive Resolution for Horn Sets","authors":"Li Dafa","doi":"10.1109/AIHAS.1992.636897","DOIUrl":"https://doi.org/10.1109/AIHAS.1992.636897","url":null,"abstract":"Let L1 v C1 and L2 V Cz be two parent clauses, where L1 and Lz are positive literals, C1 and C2 are clauses. If L1 and Lz have a most general unifier U and there is the most general substitution X such that ClaX 5 C ~ U A , then CzaX is called an inclusive resolvent of L1 v Cl and L2 v C2. The problem is whether the inclusive resolution is complete. The lifting lemma for inclusive resolution is proved, then it is proved that the inclusive resolution is complete for Horn sets. The present paper gives the inclusion algorithm, and the inclusion theorem is proved.","PeriodicalId":442147,"journal":{"name":"Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124938033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-07-08DOI: 10.1109/AIHAS.1992.636883
B. Zeigler, S. Chi
A general approach t o task-based model development is summarized in a Hierarchical Encapsulation and Abstraction Principle (HEAP) and this principle is briefly illustrated in the planning, operations and diagnosis task domains. 1 Brief Overview on Model-Base Autonomous System Architecture To cope with complex objectives, an autonomous system requires integration of symbolic and numeric data, qualitative and quantitative information, reasoning and computation. A pure AI approach is too qualitatively oriented to handle quantitative information very well. For example, classic AI planning approaches [4, 5 , 61 do not consider the timing effects, which should be of primary concern in representing our dynamic world. On the other hand, control researchers have a fairly narrow view-point, so that they mainly focus on refinement rather than robustness of a system [7], and they usually consider only the normal operational aspects of a system. However, autonomous systems have to deal with abnormal behavior of a system as well. Thus, it is crucial to have a strong formalism and an environment that allows coherent integration of symbolic and numeric informations in a valid representation process to deal with a complex dynamic world. Approaches to design various autonomous component models for planning, operation, and diagnosis have previously been developed in their respective research fields so that there are many overlaps as well as inconsistencies in assumptions. In an integrated system, such components cannot be considered independently. For example, planning requires execution, and diagnosis is activated when anomalies are detected during execution. The model-based autonomous system architecture features a model base a t the center of its planning, operation, diagnosis, and fault recovery strategies [2]. In this way, it integrates AI symbolic models and controltheoretic dynamic models into a coherent system. Endomorphism refers to the existence of a homomorphism from an object to a sub-object within it, the part (sub-object) then being a model of the whole [8]. In order to control an object, a high autonomy system needs a corresponding model of the object to determine the particular action to take. The internal model used by the system and its world base model are related by abstraction, i.e., some form of homomorphic (i.e., endomorphic relation. The inference mation for interacting with the real world object. By “world base model” we mean the most comprehensive model of the world available to the system whether it exists as a single object or as a family of partial models in the model base. Typical expert systems comprise a domainindependent inference engine and a domain-dependent knowledge base. The inference engine examines the knowledge base and decides the order in which inferences are made. The engine-based modelling approach provides a clear separation between the domain -dependent model base and the domain-independent inference engine. It facili
{"title":"Hierarchical Encapsulation and Abstraction Principle (heap) for Autonomous System Development","authors":"B. Zeigler, S. Chi","doi":"10.1109/AIHAS.1992.636883","DOIUrl":"https://doi.org/10.1109/AIHAS.1992.636883","url":null,"abstract":"A general approach t o task-based model development is summarized in a Hierarchical Encapsulation and Abstraction Principle (HEAP) and this principle is briefly illustrated in the planning, operations and diagnosis task domains. 1 Brief Overview on Model-Base Autonomous System Architecture To cope with complex objectives, an autonomous system requires integration of symbolic and numeric data, qualitative and quantitative information, reasoning and computation. A pure AI approach is too qualitatively oriented to handle quantitative information very well. For example, classic AI planning approaches [4, 5 , 61 do not consider the timing effects, which should be of primary concern in representing our dynamic world. On the other hand, control researchers have a fairly narrow view-point, so that they mainly focus on refinement rather than robustness of a system [7], and they usually consider only the normal operational aspects of a system. However, autonomous systems have to deal with abnormal behavior of a system as well. Thus, it is crucial to have a strong formalism and an environment that allows coherent integration of symbolic and numeric informations in a valid representation process to deal with a complex dynamic world. Approaches to design various autonomous component models for planning, operation, and diagnosis have previously been developed in their respective research fields so that there are many overlaps as well as inconsistencies in assumptions. In an integrated system, such components cannot be considered independently. For example, planning requires execution, and diagnosis is activated when anomalies are detected during execution. The model-based autonomous system architecture features a model base a t the center of its planning, operation, diagnosis, and fault recovery strategies [2]. In this way, it integrates AI symbolic models and controltheoretic dynamic models into a coherent system. Endomorphism refers to the existence of a homomorphism from an object to a sub-object within it, the part (sub-object) then being a model of the whole [8]. In order to control an object, a high autonomy system needs a corresponding model of the object to determine the particular action to take. The internal model used by the system and its world base model are related by abstraction, i.e., some form of homomorphic (i.e., endomorphic relation. The inference mation for interacting with the real world object. By “world base model” we mean the most comprehensive model of the world available to the system whether it exists as a single object or as a family of partial models in the model base. Typical expert systems comprise a domainindependent inference engine and a domain-dependent knowledge base. The inference engine examines the knowledge base and decides the order in which inferences are made. The engine-based modelling approach provides a clear separation between the domain -dependent model base and the domain-independent inference engine. It facili","PeriodicalId":442147,"journal":{"name":"Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129157625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-07-08DOI: 10.1109/AIHAS.1992.636869
T. Van Le
A combination of object-oriented system modelling with non-deterministic programming in Prolog results in a powerful technique of system simulation. Prolog’s unification and backtracking mechanisms are used to implement non-deterministic object select ion, multiobject accession and rendez-vous. Prolog’s secondorder predicates also facilitate the tasks of priority handling and statistics collection.
{"title":"Discrete-Event Simulation with Poss","authors":"T. Van Le","doi":"10.1109/AIHAS.1992.636869","DOIUrl":"https://doi.org/10.1109/AIHAS.1992.636869","url":null,"abstract":"A combination of object-oriented system modelling with non-deterministic programming in Prolog results in a powerful technique of system simulation. Prolog’s unification and backtracking mechanisms are used to implement non-deterministic object select ion, multiobject accession and rendez-vous. Prolog’s secondorder predicates also facilitate the tasks of priority handling and statistics collection.","PeriodicalId":442147,"journal":{"name":"Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132195782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-07-08DOI: 10.1109/AIHAS.1992.636866
Luca Spalazzi, Alessandro Cimatti, P. Traverso
I n this p a p e r we present a system (called MRG) for the development of planners that have t o work i n real-world, complex and unpredictable application domains. The i d e a underlying MRG is that domain independent problem solving architectures, instead o f featuring powerful but fixed control mechanisms, should provide powerful and flexible tools for the definition of domain dependent control mechanisms. Complex strategies and control mechanisms are uniformly represented an MRG b y tactics, explicit data structures that can be reused, modified, reasoned about and executed. A t the m o ment, MRG is being successfully used within a c o m plex real world application under development at IRS T.
{"title":"Implementing Planning As Tactical Reasoning","authors":"Luca Spalazzi, Alessandro Cimatti, P. Traverso","doi":"10.1109/AIHAS.1992.636866","DOIUrl":"https://doi.org/10.1109/AIHAS.1992.636866","url":null,"abstract":"I n this p a p e r we present a system (called MRG) for the development of planners that have t o work i n real-world, complex and unpredictable application domains. The i d e a underlying MRG is that domain independent problem solving architectures, instead o f featuring powerful but fixed control mechanisms, should provide powerful and flexible tools for the definition of domain dependent control mechanisms. Complex strategies and control mechanisms are uniformly represented an MRG b y tactics, explicit data structures that can be reused, modified, reasoned about and executed. A t the m o ment, MRG is being successfully used within a c o m plex real world application under development at IRS T.","PeriodicalId":442147,"journal":{"name":"Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132357398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-07-08DOI: 10.1109/AIHAS.1992.636882
J. M. Barone
Principled, automated procedures for assigning optimal linguistic representations to the output (or input) data space of a fuzzy control universe do not exist at the present time. This paper suggests that locating and verifying such assignments via constrained fizzy linear regression can provide the necessary foundation for their (automated) optimization. The procedure described here is related to methods for the resolution of (so-called) illposed problems and consists essentially of repeated iterations of fizzy linear regression and (crisp) linear programming operations over linguistic representations of Jicuy numbers which "cover" the raw data.. lbis paper demonstrates that a global approach to the problem of Jinding the optimal linguistic representations for raw cfuzzy control) data may prove simpler, more eflective, and more readily machine-learnable than the local approaches used heretofore.
{"title":"Determining Linguistic Models with Constrained Fuzzy Regression","authors":"J. M. Barone","doi":"10.1109/AIHAS.1992.636882","DOIUrl":"https://doi.org/10.1109/AIHAS.1992.636882","url":null,"abstract":"Principled, automated procedures for assigning optimal linguistic representations to the output (or input) data space of a fuzzy control universe do not exist at the present time. This paper suggests that locating and verifying such assignments via constrained fizzy linear regression can provide the necessary foundation for their (automated) optimization. The procedure described here is related to methods for the resolution of (so-called) illposed problems and consists essentially of repeated iterations of fizzy linear regression and (crisp) linear programming operations over linguistic representations of Jicuy numbers which \"cover\" the raw data.. lbis paper demonstrates that a global approach to the problem of Jinding the optimal linguistic representations for raw cfuzzy control) data may prove simpler, more eflective, and more readily machine-learnable than the local approaches used heretofore.","PeriodicalId":442147,"journal":{"name":"Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128579104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-07-08DOI: 10.1109/AIHAS.1992.636886
A. Travers, T. C. Ly
Goal achievement is a fundamental aspect of developing an autonomous agent. The environment in which this goal is to be achieved greatly affects the subsequent design. In one such environment -- dynamic, complex and unknown the design concentrates on survival. A reactive planner is proposed as a mechanism for maintaining the balance between goal achievement and survival. The mechanism for survival concentrates on simple, low-level information and decision making. This information is provided by a Message Passing system that controls the flow of information.
{"title":"Reactive Planning and Mps: Two Pieces to the Autonomous Puzzle?","authors":"A. Travers, T. C. Ly","doi":"10.1109/AIHAS.1992.636886","DOIUrl":"https://doi.org/10.1109/AIHAS.1992.636886","url":null,"abstract":"Goal achievement is a fundamental aspect of developing an autonomous agent. The environment in which this goal is to be achieved greatly affects the subsequent design. In one such environment -- dynamic, complex and unknown the design concentrates on survival. A reactive planner is proposed as a mechanism for maintaining the balance between goal achievement and survival. The mechanism for survival concentrates on simple, low-level information and decision making. This information is provided by a Message Passing system that controls the flow of information.","PeriodicalId":442147,"journal":{"name":"Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128023709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-07-08DOI: 10.1109/AIHAS.1992.636876
K. Wong
Modem power systems become more and more complex and electrical networks become highly interconnected as the demands of electricity grow due to thie progress of society. There is a need for modem power systems to generate and to supply high quality electric energy to customers with very high degree of security. To achieve this requirement, in the last three decades, power engineers Pave employed computers to assist them to analyse, to plan and to operate power systems.
{"title":"Artificial Intelligence Applications in Power Systems","authors":"K. Wong","doi":"10.1109/AIHAS.1992.636876","DOIUrl":"https://doi.org/10.1109/AIHAS.1992.636876","url":null,"abstract":"Modem power systems become more and more complex and electrical networks become highly interconnected as the demands of electricity grow due to thie progress of society. There is a need for modem power systems to generate and to supply high quality electric energy to customers with very high degree of security. To achieve this requirement, in the last three decades, power engineers Pave employed computers to assist them to analyse, to plan and to operate power systems.","PeriodicalId":442147,"journal":{"name":"Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123363817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-07-08DOI: 10.1109/AIHAS.1992.636892
P. Rives, R. Pissard-Gibollet
This paper deals with vision based control applied to autonomous mobile robots. The general a proach in robot vision separates vision from control htat ic look and move). A n alternative way consists to specify the problem tn terms of control directly into the sensor frame. This approach seems t o be Q fruitful way for implementing robotics tasks based on reactivity concept. We introduce a low level task specification b y the notion of virtual linkage. This virtual linkage can be expressed b y a set of constraints on the motion of a frame linked to 2he robot with respecf t o a certain frame associated to the environnment. It seems interesting to apply such a vision based control to a mobile robot. The robot considered here is a two wheels driven nonholonomic car? with a camera mounted on 3 d.0.f manipulator. In this siudy we consider the whole mechanical system constituted by the cart and i f s manipulator like a single kinematic chain. So in adding the degrees of freedoom of the a m i o the cart, it becomes possible to fully control the trajectory of the effector. In order to validate this approach, a simulation loo1 has been developped in Mathematica. A first application concerns automatic exploration and cartography of an unknowm room by wall following techniques.
{"title":"Reactive Mobile Robots Based on a Visual Servoing Approach","authors":"P. Rives, R. Pissard-Gibollet","doi":"10.1109/AIHAS.1992.636892","DOIUrl":"https://doi.org/10.1109/AIHAS.1992.636892","url":null,"abstract":"This paper deals with vision based control applied to autonomous mobile robots. The general a proach in robot vision separates vision from control htat ic look and move). A n alternative way consists to specify the problem tn terms of control directly into the sensor frame. This approach seems t o be Q fruitful way for implementing robotics tasks based on reactivity concept. We introduce a low level task specification b y the notion of virtual linkage. This virtual linkage can be expressed b y a set of constraints on the motion of a frame linked to 2he robot with respecf t o a certain frame associated to the environnment. It seems interesting to apply such a vision based control to a mobile robot. The robot considered here is a two wheels driven nonholonomic car? with a camera mounted on 3 d.0.f manipulator. In this siudy we consider the whole mechanical system constituted by the cart and i f s manipulator like a single kinematic chain. So in adding the degrees of freedoom of the a m i o the cart, it becomes possible to fully control the trajectory of the effector. In order to validate this approach, a simulation loo1 has been developped in Mathematica. A first application concerns automatic exploration and cartography of an unknowm room by wall following techniques.","PeriodicalId":442147,"journal":{"name":"Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132608288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-07-08DOI: 10.1109/AIHAS.1992.636885
P. Mourou, B. Fade
{"title":"Multi-Agent Planning and Execution Monitoring : Application to Highway Traffic","authors":"P. Mourou, B. Fade","doi":"10.1109/AIHAS.1992.636885","DOIUrl":"https://doi.org/10.1109/AIHAS.1992.636885","url":null,"abstract":"","PeriodicalId":442147,"journal":{"name":"Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128313307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-07-08DOI: 10.1109/AIHAS.1992.636881
S. Chakravarthy, C. Nayar
The principal application of distance relays is for the protection of essential sub-transmission and transmission lines operating at EHV / UHV voltages. The performance of transmission lines depend on its parameters which in turn depend on various factors leading to a wide range of possible magnitudes. The response of distance relays for a selected operating characteristics is therefore unpredictable when a fault occurs. Although over the years different operating characteristics have been in use, there is a need for an adaptive operating characteristic, which is the subject of the paper.
{"title":"The Application of Pattern Recognition in Distance Relaying","authors":"S. Chakravarthy, C. Nayar","doi":"10.1109/AIHAS.1992.636881","DOIUrl":"https://doi.org/10.1109/AIHAS.1992.636881","url":null,"abstract":"The principal application of distance relays is for the protection of essential sub-transmission and transmission lines operating at EHV / UHV voltages. The performance of transmission lines depend on its parameters which in turn depend on various factors leading to a wide range of possible magnitudes. The response of distance relays for a selected operating characteristics is therefore unpredictable when a fault occurs. Although over the years different operating characteristics have been in use, there is a need for an adaptive operating characteristic, which is the subject of the paper.","PeriodicalId":442147,"journal":{"name":"Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121731349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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