© 1998 Singh & Huhns1 Cooperative Information Systems Michael N. Huhns

© 1998 Singh & Huhns2 Open Environments: Characteristics Cross enterprise boundaries Comprise autonomous resources that –Involve loosely structured addition and removal –Range from weak to subtle consistency requirements –Involve updates only under local control –Frequently involve nonstandard data Have intricate interdependencies

© 1998 Singh & Huhns3 Open Environments: Technical Challenges Coping with scale Respecting autonomy Accommodating heterogeneity Maintaining coordination Getting work done –Acquiring, managing, advertising, finding, fusing, and using information over uncontrollable environments

© 1998 Singh & Huhns4 What is an Agent? The term agent in computing covers a wide range of behavior and functionality. We shall review this range in a later section In general, an agent is an active computational entity –with a persistent identity –that can perceive, reason about, and initiate activities in its environment –that can communicate (with other agents) It is the last feature that makes agents a worthwhile metaphor in computing

© 1998 Singh & Huhns5 What is CIS? CIS is concerned with how decentralized information system components, consisting of resources, applications, and human-computer interfaces, should coordinate their activities to achieve their goals. When pursuing common or overlapping goals, they should act cooperatively so as to accomplish more as a group than individually; when pursuing conflicting goals, they should compete intelligently You know a CIS system by its –decentralization –complex components, best described at the knowledge level –complex interactions –adaptive behavior and, sometimes, –coordination

© 1998 Singh & Huhns6 Economics Heritage of CIS Cognitive Science Linguistics Databases Sociology Psychology Systems Theory Distributed Computing Cooperative Information Systems Most work

© 1998 Singh & Huhns7 Dimensions of Abstraction/1 Information resources are associated with abstractions over different dimensions. These may be thought of as constraints that must be discovered and represented Structure –schemas and views, e.g., securities are stocks –specializations and generalizations of domain concepts, e.g., stocks are a kind of liquid asset –value maps, e.g., S&P A+ rating corresponds to Moody’s A rating –semantic data properties, sufficient to characterize the value maps, e.g., prices on the Madrid Exchange are daily averages rather than closing prices –cardinality constraints –integrity constraints, e.g., each stock must have a unique SEC identifier

© 1998 Singh & Huhns8 Dimensions of Abstraction/2 Data –domain specifications –value ranges, e.g., Price >+= 0 –allow/disallow “maybe” values Process –procedures, i.e., how to process information (e.g., how to decide what stock to recommend) –preferences for accesses and updates in case of data replication (based on recency or accuracy of data) –preferences to capture view update semantics –contingency strategies, e.g., whether to ignore, redo, or compensate –contingency procedures, i.e., how to compensate transactions –flow, e.g., where to forward requests or results –temporal constraints, e.g., must report tax data every quarter

© 1998 Singh & Huhns9 Dimensions of Abstraction/3 Policy –security, i.e., who has rights to access or update what information? (e.g., customers can access all of their accounts, except blind trusts) –authentication, i.e., a sufficient test to establish identity (e.g., passwords, retinal scans, or smart cards) –bookkeeping (e.g., logging all accesses)

© 1998 Singh & Huhns10 Characteristics of CIS Applications Inappropriate for conventional distributed processing: –local data may be incomplete or inaccurate –local problem solving is prone to error –the nodes are complex enough to be agents Inappropriate for conventional AI: –local autonomy is critical –strong semantic constraints exist among agents Complexity Number of agents

© 1998 Singh & Huhns11 Examples of CIS Applications Semantic integration of heterogeneous resources –Tools to capture requirements –Systems to execute those requirements Information access over loosely-coupled systems, e.g., the Internet Most effort in interoperability of existing or separately developed applications; hardly any effort in new applications per se Schema integration Integration of business procedures –Legacy applications abound

© 1998 Singh & Huhns12 CIS Advantages over DC CIS is a subclass of DC with the following features: High-level messages lead to –lower communication costs –easy reimplementability –more concurrency Autonomy at the knowledge level leads to –lower synchronization costs Intelligence embedded at each site leads to –increased robustness

© 1998 Singh & Huhns13 Benefits of CIS Due to Distributed Computing –Modularity: many problems are inherently decentralized; large problems are easier if they are decomposed and distributed –Speed –Reliability Due to AI –Maintaining systems becomes harder as they scale up sometimes you want to mix and match parts--easy, if they were designed to cooperate sometimes you want to extend capabilities: easier if you can just add more players to a team –Knowledge acquisition: use many narrow experts –Reusability –Ease of requirements acquisition –Platform independence

© 1998 Singh & Huhns14 When Is CIS Appropriate? When information is distributed, as in office automation When metadata is heterogeneous, as in schema integration When autonomous applications are to be integrated, as in legacy systems When data sources are distributed, as in traffic management When expertise is distributed, as in healthcare systems When rewards are distributed, as in automated markets When diverse interests must be represented, as in electronic commerce

© 1998 Singh & Huhns15 When Is CIS Appropriate? When decisions are distributed, as in manufacturing control When independently developed knowledge bases must be interconnected When resources and actions are distributed

© 1998 Singh & Huhns16 CIS Application: Office Workflow The claims department of an insurance company processes claims by routing them electronically among appropriate clerical workers. Unfortunately, the system cannot handle exceptions to the normal workflow. Expert systems assisting each clerical worker could aid in this, but they would be more effective if they could communicate their intentions to each other [exception conditions]

© 1998 Singh & Huhns17 CIS Application: Software Maintenance DBs are replicated at the schema level at several sites. However, fields are overloaded differently at each site. Imagine that the schemas are described by a set of beliefs, and that changes are justified by the beliefs. A distributed truth-maintenance system could maintain the consistency of such beliefs, thereby restoring the compatibility of the databases [semantic mismatch]

© 1998 Singh & Huhns18 CIS Application: Automated Markets A mail-order hardware retailer sells its own brand of wrenches. It asks its suppliers for particular kinds of wrenches whose demand is high. It would like to achieve this through an automated system, which requests bids for each kind of wrench that has low inventory –gathers and evaluates bids –negotiates as necessary with the more promising suppliers,and –places orders [representing autonomous interests]

© 1998 Singh & Huhns19 CIS Application: Manufacturing Control An automotive parts manufacturer uses a decision-support system to schedule down-time for machine tools. Independently, each machining operation is monitored for the parts produced, so that the tool may be replaced when too many parts fall out of tolerance When a tool is taken off-line, upstream parts pile up and downstream parts dry up. The systems should communicate the nature and expected extent of the down-time [distributed decision-making]

© 1998 Singh & Huhns20 CIS Application: Process Control One chemical process supplies a solvent needed by a second chemical process. The process controllers are written in the same language and run on identical computers. The computers are linked by Ethernet. However, when the first process is shut down, the second process may not learn about it until the solvent suddenly stops flowing. This can prove expensive [homogeneity of platforms is insufficient]

© 1998 Singh & Huhns21 Dimensions of CIS: System Scale is the number of agents: Interactions: Coordination (self interest): Agent Heterogeneity: Communication Paradigm: IndividualCommitteeSociety ReactivePlanned AntagonisticAltruisticCollaborative CompetitiveCooperativeBenevolent IdenticalUnique Point-to-PointMulticast by name/roleBroadcast

© 1998 Singh & Huhns22 Dimensions of CIS: Agent Dynamism is the ability of an agent to learn: Autonomy: Interactions: Sociability (awareness): FixedTeachableAutodidactic ControlledIndependent SimpleComplex Interdependent AutisticCollaborativeCommitting

© 1998 Singh & Huhns23 Basic Problems of CIS 1.Description, decomposition, and distribution of tasks among agents 2.Interaction and communication among agents 3.Distribution of control among agents 4.Representation of goals, problem-solving states, and other agents 5.Rationality, maintenance of consistent beliefs, and reconciliation of conflicts among agents

© 1998 Singh & Huhns24 2. ENTERPRISE INTEGRATION

© 1998 Singh & Huhns25 Enterprise Modeling Model static and dynamic aspects of enterprises Models document business functions –databases –applications –knowledge bases –workflows, and the information they create, maintain, and use –the organization itself Models enable –reusability –integrity validation –consistency analysis –change impact analysis –automatic database and application generation

© 1998 Singh & Huhns26 Building Information Systems Cognition Universe of Discourse 1 Conceptual Schema CASE Tool Interface Application Database usegenerate construct observe

© 1998 Singh & Huhns27 Cooperating Information Systems Ontology: a representation of knowledge specific to some universe(s) of discourse Cognition Universe of Discourse 1 Conceptual Schema CASE Tool Interface Application Database usegenerate Cognition Conceptual Schema CASE Tool Interface Application Database usegenerate Universe of Discourse 2 Ontology construct observe

© 1998 Singh & Huhns28 Cooperation in Information Systems Connectivity: ISs with the ability to exchange messages Interoperability: ISs with the ability to exchange messages to request and receive services from each other, i.e., use each other’s functionality Cooperation: ISs interoperating to execute tasks jointly

© 1998 Singh & Huhns29 Cooperating Information Systems Hospital CIS Doctor’s CIS Insurance CIS Clinic/HMO CIS Lab data Claims Accounting

© 1998 Singh & Huhns30 Information System Architectures: Centralized Mainframe Terminal3270 Terminal

© 1998 Singh & Huhns31 Information System Architectures: Client-Server Server Web Server Database Server PC Client PC Client PC Client Workstation Client Master-Slave

© 1998 Singh & Huhns32 Information System Architectures: Distributed System Web System Database System Application Peer-to-Peer

© 1998 Singh & Huhns33 Information System Architectures: Cooperative System Web System Database System Application (Mediators, Proxies, Aides, Wrappers) Agent