SOFTWARE AGENTS

Shivam Seth (205114005)Rajesh Kumar (205114006)

Ajay Tiwari (205114007) Sahil Gupta (205114008)

Vijay Srivastava (205114009)Date : 18-July-2016

INTERFACE AGENTMETAPHOR WITH CHARACTER

CONTENTS Introduction to interface agents…

Why interface agents…

Personal Assistant metaphor…

Problems in building interface agents.

Opt 1: User programmed agent

Opt 2: Agents with extensive knowledge.

Opt 3: Interface agents.

Learning Nodes…

Applications…

Example & Problems…

Interface agents… Introduction• Emphasise autonomy and learning in order to perform

tasks for their owners.• Support and provide proactive assistance to a human

that is using a particular application or solving a certain problem • Anticipate user needs • Make suggestions • Provide advice

… without explicit user requests

Interface agents…WHY….. ??

Direct manipulation Interface AgentsThe computer is merely a passive entity waiting to execute detailed instructions

The user and the agent engage in a cooperative process

The user gives commands by operations on the interface objects through input devices

Software agents ‘know’ user’s interests and can act autonomously on their behalf

Interface objects represent software functions and objects

(sometimes) agents appear as ‘living’ entities with animated facial expression or body language

Initially, a personal assistant is not very familiar with the habits and preferences of his employer • It may not be very helpful • It may even give extra work !

With every experience, the assistant learns • watching how the employer performs tasks • receiving instructions from the employer • learning from other more experienced assistants Gradually, more tasks that were initially directly performed by the employer can be taken care of by the assistant

Interface agents…Personal Assistant Metaphor

Interface agents…Problems in Building…

Competence: How does an agentacquire the knowledge it needs to decide: • when to help the user • what to help the user with • how to help

Trust: How can we guarantee the user feels comfortable delegating tasks to an agent?

Interface agents…1. User programmed Agent…

Idea: use a collection of user-programmed rules for processing information related to a particular task Example: E-Mail System, ATM system.Once created, these rules perform tasks for the user without having to be explicitly invoked by the user with the arrival of each new message

Analysis: Competence: Not satisfactory No adaption to new situations Trust: not a problem in this case, as agents don’t learn and don’t have proactivity

Interface agents…2. Agents with extensive knowledge.. Idea: At runtime, the agent uses its knowledge to recognise the user’s intentions and to find opportunities for contributing with help, advices, suggestions ... Example: Video Games (eg Chess), Online Shopping PortalsDoes reasoning and planning• Volunteer information proactively• Correct a user’s misconceptions Analysis: Competence:• Requires a huge amount of work from knowledge engineer • Knowledge is fix once for all, cannot be customised to individual

users Trust: The user may feel loss of control and understanding

Interface agents…

Interface agents…Basic Hypothesis…

Under certain conditions, an interface agent can acquire (automatically) the knowledge it needs to assist its user.

Repetition: The use of the application has to involve a substantial amount of repetitive behaviour either within the actions of one user or among users Variance: The repetitive behaviour is potentially different for different users

Interface agents…Learning Nodes… Learning from the user • by observing and imitating the user• by receiving positive and negative feedback

from the user • by receiving explicit instructions from the user

Learning from other agents • asking other agents for advice

Interface agents…Rationale…

Less work for the end user and for the application developer • Automation of routine activities • Automation of tasks that would take a long time to a

human user The agent can adapt, over time, to its user’s preferences and habits • Learn automatically user profiles, adapted to the user

needs • The profile of a user can change dynamically

Interface agents…Rationale…

Know-how among different users in a community may be shared • Communication and (limited) cooperation

between interface agents of different users

Use in applications with repetitive behaviour• Even if the behaviour is different for each user

Interface agents…Applications….

• Mail management • Scheduling meetings • News filtering agent• Buying/selling on user’s behalf • Internet browsing…. Many More

Interface agents…Example in Detail….

• Learn user preferences on different kinds of meetings

• Make a meeting proposal • Accept a meeting proposal • Reject a meeting proposal • Reschedule a previously agreed meeting

Negotiate a meeting time with other agents

Meeting Scheduler

Interface agents…Problems Personal Assistant…

Slow learning curve • Agents require many examples before they can make

accurate predictions (especially if they cannot be directly trained)

• No useful assistance during the learning processLearning from scratch • Each agent has to learn on its own, even if there is a

bunch of agents dealing with a team of people with similar interests

Difficulty to adapt to completely new situations

Referenceshttp://www.sce.carleton.ca/netmanage/docs/AgentsOverview/ao.html

Jeffrey M.Bradshaw, An Introduction to Software Agents, MIT Press, USA 1997

Thank You!