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Group 1 (3009, 01, 02, 03, 04) interacting with agents, direct manipulation to delegation

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Prateek Soni

This document discusses agents and how humans interact with them, moving from direct manipulation to delegation. It defines agents and their key properties such as reactivity, proactiveness, and social ability. Delegation is described as assigning responsibility to another, such as an intelligent software agent, to perform tasks. The benefits of delegation for both managers and employees are outlined. Finally, the document details the steps involved in effective delegation, including introducing the task, demonstrating it clearly, ensuring understanding, allocating authority and resources, letting go, and providing support and monitoring.

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CA 7B3 SOFTWARE AGENTS
INTERACTING WITH AGENTS AGENT FROM DIRECT MANIPULATION TO DELEGATION Presenters: BHEEMRAJ SAINI 205113009 SRISHTI GUPTA 205114001 AJAY BENIWAL 205114002 AKHILESH CHOUDHARY 205114003 PARAKH KUMAR RAHANGDALE 205114004 Date: July 18, 2016
What is an Agent?What is an Agent? An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors.
Formal DefinitionsFormal Definitions Autonomous agents are computational systems that inhabit some complex dynamic environment, sense and act autonomously in this environment, and by doing so realize a set of goals or tasks for which they are designed. [Maes, 1995] Intelligent agents continuously perform three functions: perception of dynamic conditions in the environment; action to affect conditions in the environment; and reasoning to interpret perceptions, solve problems, draw inferences, and determine actions. [Hayes- Roth, 1995]
Agents PropertiesAgents Properties [Brenner et al., 1998]
ReactivityReactivity A reactive system is one that maintains an ongoing interaction with its environment, and responds to changes that occur in it (in time for the response to be useful)
ProactivenessProactiveness Reacting to an environment is easy (e.g., stimulus response rules) But we generally want agents to do things for us Hence goal directed behavior Pro-activeness = generating and attempting to achieve goals; not driven solely by events; taking the initiative
Social AbilitySocial Ability The real world is a multi-agent environment: we cannot go around attempting to achieve goals without taking others into account Some goals can only be achieved with the cooperation of others Social ability in agents is the ability to interact with other agents (and possibly humans) via some kind of agent-communication language, and perhaps cooperate with others
Other PropertiesOther Properties Mobility: the ability of an agent to move around an electronic network Veracity honesty: an agent will not knowingly communicate false information Benevolence kind: agents do not have conflicting goals, and that every agent will therefore always try to do what is asked of it Rationality: agent will act in order to achieve its goals, and will not act in such a way as to prevent its goals being achieved - at least insofar as its beliefs permit Learning/adaption: agents improve performance over time
CharacteristicsCharacteristics Cooperation (Proactive) Autonomy Adaptation (Learning) Smart agent [Nwana, 1996]
Adaptation Agents adapt to their environment and users and learn from experience. Via machine learning, knowledge discovery, data mining, etc. Situated in and aware of their environment Cooperation Autonomy Adaptation
Cooperation Agents use standard languages and protocols to cooperate and collaborate to achieve common goals. Cooperate with human agents and other software agents Supported by agent communication languages and protocols. Consistent with human conventions and intuition. Cooperation Autonomy Adaptation
Autonomy Agents act autonomously to pursue their agenda. Goal directed behavior Cooperation Autonomy Adaptation
Task Modeling in Intelligent AgentsTask Modeling in Intelligent Agents Before we design an intelligent agent, we must specify its task environment: PEAS: Performance measure Environment Actuators Sensors
PEAS Description of Task Environments Performance Measures Environment Actuators Sensors used for high-level characterization of agents determine the actions the agent can perform surroundings beyond the control of the agent used to evaluate how well an agent solves the task at hand provide information about the current state of the environment
Example: Agent = Taxi DriverExample: Agent = Taxi Driver Performance measure: Safe, fast, legal, comfortable trip, maximize profits Environment: Roads, other traffic, pedestrians, customers Actuators: Steering wheel, accelerator, brake, signal, horn Sensors: Cameras, speedometer, GPS, odometer, engine sensors
Example: Agent = Medical DiagnosisExample: Agent = Medical Diagnosis SystemSystem Performance measure: Correct Diagnosis, minimize costs Environment: Patient, hospital, staff Actuators: Screen display (questions, tests, diagnoses, treatments, referrals) Sensors: Keyboard (entry of symptoms, findings, patient's answers)
How Might People Interact with Agents? How will intelligent agents interact with people and perhaps more important, how might people think about agents? Agents might set up schedules, reserve hotel and meeting rooms, arrange transportation, and even outline meeting topics, all without human intervention.
Safety Making sure that the agent does not do things that would jeopardize the physical, mental, or monetary well-being of the owner. The sense of control, but because the technical and social implications are considerably different, it deserves its own special consideration. Privacy and confidentiality of actions will be among the major issues confronting the use of intelligent agents in our future of a fully interconnected, fully communicating society. Privacy
Human-Agent Interaction The manner by which the person's conceptual model of the agent's method of operation and activities is presented, and the manner by which the agent offers advice and information to the person.
What is Delegation? Delegation is the assignment of responsibility to another person for the purpose of carrying out specific job-related activities. Delegation is a shift of decision-making authority from one organizational level to another.
Elements of Delegation a 'principal' An individual who delegates authority over a particular policy area (or function) to another an 'agent'. The other person who receives the delegated authority
Knowing When to Delegate Delegating can be especially helpful in the following situations: When the task offers valuable training to an employee When an employee has more knowledge or experience related to the task than you When the task is recurring and all employees should be prepared or trained When the task is of low priority and you have high priority tasks that require your immediate attention
To Whom Should You Delegate? When deciding who to select for the task, you must consider: The current work load of the employee The employees strengths and weaknesses The training and experience levels of the employee
Agent from Direct Manipulation to Delegation Delegation gives users the option to offload tasks to software systemsagentsthat perform the tasks for the user. This enables users to perform tasks that are difficult to perform using graphical user interfaces, tasks such as searching and retrieving data in large distributed networks
Benefits of Delegation Manager / Supervisor Benefits Reduced stress Improved time management Increased trust Employee Benefits Professional knowledge and skill development Elevated self-esteem and confidence Sense of achievement Organizational Benefits Increased teamwork Increased productivity and efficiency
Steps in Delegation I Introduce the task D- Demonstrate clearly what needs to be done E - Ensure understanding A - Allocate authority, information and resources L - Let go S - Support and Monitor
Introduce the Task Determine the task to be delegated Determine the tasks to retain Select the delegate
Demonstrate Clearly Show examples of previous work Explain objectives Discuss timelines, set deadlines
Ensure Understanding Clear communication Ask for clarification Secure commitment
Allocate authority, information, resources Provide access to all information sources Provide appropriate training to ensure success
Let go Communicate delegates authority Step back, let them work
Support and Monitor Schedule follow-up meetings Review progress Assist, when requested Avoid interference Publicly praise progress and completion Encourage problem solving
References [1]: Jeffrey M. Bradshaw, Software Agents, MIT Press, 2000 [2]: http://www.javaworld.com/javaworld/jw-04-1997/jw-04-agents.html [3]: http://www.msci.memphis.edu/~franklin/AgentProg.html [4]: http://www.javaworld.com/javaworld/jw-04-1997/jw-04-hood.html [5]: http://www.trl.ibm.co.jp/aglets/JAAPI-whitepaper.html [6]: http://luckyspc.lboro.ac.uk/Docs/Papers/Mesela97.html [7]: http://www.javaworld.com/javaworld/jw-05-1997/jw-05-hood.html [8]: http://www.trl.ibm.co.jp/aglets/whitepaper.htm [9]: http://www.networking.ibm.com/iag/iaghome.html#new

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Group 1 (3009, 01, 02, 03, 04) interacting with agents, direct manipulation to delegation

  • 2. INTERACTING WITH AGENTS AGENT FROM DIRECT MANIPULATION TO DELEGATION Presenters: BHEEMRAJ SAINI 205113009 SRISHTI GUPTA 205114001 AJAY BENIWAL 205114002 AKHILESH CHOUDHARY 205114003 PARAKH KUMAR RAHANGDALE 205114004 Date: July 18, 2016
  • 3. What is an Agent?What is an Agent? An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors.
  • 4. Formal DefinitionsFormal Definitions Autonomous agents are computational systems that inhabit some complex dynamic environment, sense and act autonomously in this environment, and by doing so realize a set of goals or tasks for which they are designed. [Maes, 1995] Intelligent agents continuously perform three functions: perception of dynamic conditions in the environment; action to affect conditions in the environment; and reasoning to interpret perceptions, solve problems, draw inferences, and determine actions. [Hayes- Roth, 1995]
  • 6. ReactivityReactivity A reactive system is one that maintains an ongoing interaction with its environment, and responds to changes that occur in it (in time for the response to be useful)
  • 7. ProactivenessProactiveness Reacting to an environment is easy (e.g., stimulus response rules) But we generally want agents to do things for us Hence goal directed behavior Pro-activeness = generating and attempting to achieve goals; not driven solely by events; taking the initiative
  • 8. Social AbilitySocial Ability The real world is a multi-agent environment: we cannot go around attempting to achieve goals without taking others into account Some goals can only be achieved with the cooperation of others Social ability in agents is the ability to interact with other agents (and possibly humans) via some kind of agent-communication language, and perhaps cooperate with others
  • 9. Other PropertiesOther Properties Mobility: the ability of an agent to move around an electronic network Veracity honesty: an agent will not knowingly communicate false information Benevolence kind: agents do not have conflicting goals, and that every agent will therefore always try to do what is asked of it Rationality: agent will act in order to achieve its goals, and will not act in such a way as to prevent its goals being achieved - at least insofar as its beliefs permit Learning/adaption: agents improve performance over time
  • 11. Adaptation Agents adapt to their environment and users and learn from experience. Via machine learning, knowledge discovery, data mining, etc. Situated in and aware of their environment Cooperation Autonomy Adaptation
  • 12. Cooperation Agents use standard languages and protocols to cooperate and collaborate to achieve common goals. Cooperate with human agents and other software agents Supported by agent communication languages and protocols. Consistent with human conventions and intuition. Cooperation Autonomy Adaptation
  • 13. Autonomy Agents act autonomously to pursue their agenda. Goal directed behavior Cooperation Autonomy Adaptation
  • 14. Task Modeling in Intelligent AgentsTask Modeling in Intelligent Agents Before we design an intelligent agent, we must specify its task environment: PEAS: Performance measure Environment Actuators Sensors
  • 15. PEAS Description of Task Environments Performance Measures Environment Actuators Sensors used for high-level characterization of agents determine the actions the agent can perform surroundings beyond the control of the agent used to evaluate how well an agent solves the task at hand provide information about the current state of the environment
  • 16. Example: Agent = Taxi DriverExample: Agent = Taxi Driver Performance measure: Safe, fast, legal, comfortable trip, maximize profits Environment: Roads, other traffic, pedestrians, customers Actuators: Steering wheel, accelerator, brake, signal, horn Sensors: Cameras, speedometer, GPS, odometer, engine sensors
  • 17. Example: Agent = Medical DiagnosisExample: Agent = Medical Diagnosis SystemSystem Performance measure: Correct Diagnosis, minimize costs Environment: Patient, hospital, staff Actuators: Screen display (questions, tests, diagnoses, treatments, referrals) Sensors: Keyboard (entry of symptoms, findings, patient's answers)
  • 18. How Might People Interact with Agents? How will intelligent agents interact with people and perhaps more important, how might people think about agents? Agents might set up schedules, reserve hotel and meeting rooms, arrange transportation, and even outline meeting topics, all without human intervention.
  • 19. Safety Making sure that the agent does not do things that would jeopardize the physical, mental, or monetary well-being of the owner. The sense of control, but because the technical and social implications are considerably different, it deserves its own special consideration. Privacy and confidentiality of actions will be among the major issues confronting the use of intelligent agents in our future of a fully interconnected, fully communicating society. Privacy
  • 20. Human-Agent Interaction The manner by which the person's conceptual model of the agent's method of operation and activities is presented, and the manner by which the agent offers advice and information to the person.
  • 21. What is Delegation? Delegation is the assignment of responsibility to another person for the purpose of carrying out specific job-related activities. Delegation is a shift of decision-making authority from one organizational level to another.
  • 22. Elements of Delegation a 'principal' An individual who delegates authority over a particular policy area (or function) to another an 'agent'. The other person who receives the delegated authority
  • 23. Knowing When to Delegate Delegating can be especially helpful in the following situations: When the task offers valuable training to an employee When an employee has more knowledge or experience related to the task than you When the task is recurring and all employees should be prepared or trained When the task is of low priority and you have high priority tasks that require your immediate attention
  • 24. To Whom Should You Delegate? When deciding who to select for the task, you must consider: The current work load of the employee The employees strengths and weaknesses The training and experience levels of the employee
  • 25. Agent from Direct Manipulation to Delegation Delegation gives users the option to offload tasks to software systemsagentsthat perform the tasks for the user. This enables users to perform tasks that are difficult to perform using graphical user interfaces, tasks such as searching and retrieving data in large distributed networks
  • 26. Benefits of Delegation Manager / Supervisor Benefits Reduced stress Improved time management Increased trust Employee Benefits Professional knowledge and skill development Elevated self-esteem and confidence Sense of achievement Organizational Benefits Increased teamwork Increased productivity and efficiency
  • 27. Steps in Delegation I Introduce the task D- Demonstrate clearly what needs to be done E - Ensure understanding A - Allocate authority, information and resources L - Let go S - Support and Monitor
  • 28. Introduce the Task Determine the task to be delegated Determine the tasks to retain Select the delegate
  • 29. Demonstrate Clearly Show examples of previous work Explain objectives Discuss timelines, set deadlines
  • 30. Ensure Understanding Clear communication Ask for clarification Secure commitment
  • 31. Allocate authority, information, resources Provide access to all information sources Provide appropriate training to ensure success
  • 32. Let go Communicate delegates authority Step back, let them work
  • 33. Support and Monitor Schedule follow-up meetings Review progress Assist, when requested Avoid interference Publicly praise progress and completion Encourage problem solving
  • 34. References [1]: Jeffrey M. Bradshaw, Software Agents, MIT Press, 2000 [2]: http://www.javaworld.com/javaworld/jw-04-1997/jw-04-agents.html [3]: http://www.msci.memphis.edu/~franklin/AgentProg.html [4]: http://www.javaworld.com/javaworld/jw-04-1997/jw-04-hood.html [5]: http://www.trl.ibm.co.jp/aglets/JAAPI-whitepaper.html [6]: http://luckyspc.lboro.ac.uk/Docs/Papers/Mesela97.html [7]: http://www.javaworld.com/javaworld/jw-05-1997/jw-05-hood.html [8]: http://www.trl.ibm.co.jp/aglets/whitepaper.htm [9]: http://www.networking.ibm.com/iag/iaghome.html#new