1. Agent-based Interfaces u0423507 u0526893 u0422533

2. Software Agents act on behalf of people in the electronic world. Agents can perform repetitive tasks E.g. Web crawlers and e-mail filters

3. Agents can learn from user’s actions Difficult to find a language suitable for user and agent User may not receive immediate feedback

4. Apple HyperCard: earliest example of AI Agent learning based on user actions. Eager had a clear ‘embodiment’, the cat on screen User free to ignore agent

5. MS Excel, intelligent functions but diffused, not embodied. Office assistant

6. Agent-based systems include aspects of both language and action paradigms. Old command based systems acted as intermediaries. Agents act on the user’s behalf

7. Direct manipulation emphasises the user’s own actions. The Agent is usually acting in an environment the user can also act upon.

8. The End