52, Argumentative Agent Deliberation, Roles and Context

This paper ('Argumentative Agent Deliberation, Roles and Context', 2002, Antonis Kakas and Pavlos Moraitis) presents an argumentation based framework based on 'Logic Programming without Negation as Failure' that makes use of three levels of rules (in the examples at least); 'object-level decision rules', 'role (or default context) priorities' and '(specific) context priorities'. Hints at using abduction for agents to make assumptions under incomplete knowledge but I didn't quite get it. Good deliberation examples making use of rules, priorities over rules and priorities over priorities over rules.

Deliberation Examples

I need to think of an example for a multi-agent deliberation-like dialogue to include in a forthcoming paper. Here are some first tries:

--- 1 ---

swapAppointments(Ag1,Ag2,App1,App2) <- requires(Ag1,Req1), fulfils(App2,Req1), has(Ag1,App1), ¬fulfils(App1,Req1), canSwap(Ag2,App2,App1)

cantSwap(Ag,App1,App2) <- ¬has(Ag,App1)

cantSwap(Ag,App1,App2) <- has(Ag,App1), requires(Ag,Req), fulfils(App1,Req), ¬fulfils(App2,Req)

Assumptions = {¬fulfils(App,Req), canSwap(Ag,App1,App2)}

Contrary(¬fulfils(App,Req)) = fulfils(App,Req)
Contrary(canSwap(Ag,App1,App2)) = cantSwap(Ag,App1,App2)

Consider two concrete agents, ag1 and ag2, with initial private beliefs as follows:
Priv(ag1) = {has(ag1,app1), requires(ag1,fridayAppointment), fulfils(app1,morningAppointment), fulfils(app2,fridayAppointment)}
Priv(ag2) = {has(ag2,app2), requires(ag2,morningAppointment), fulfils(app2,morningAppointment)}

--- 2 ---

buy(House) <- withinBudget(House), goodLocation(House)

badLocation(House) <- farFromWork(House), badTransportLinks(House)

goodTransportLinks(House) <- nearBusStop(House), frequentBusService(House)

Assumptions = {goodLocation(House), badTransportLinks(House), frequentBusService(House)}

Contrary(goodLocation(House)) = badLocation(House)

Contrary(badTransportLinks(House)) = goodTransportLinks(House)

Contrary(frequentBusService(House)) = infrequentBusService(House)

Consider two concrete agents, ag1 and ag2, with initial private beliefs as follows:
Priv(ag1) = {withinBudget(house1), nearBusStop(house1)}
Priv(ag2) = {farFromWork(house1)}

--- 3 ---

watch(Ag1,Ag2,Film) <- criticallyAcclaimed(Film), willLike(Ag1,Film), willLike(Ag2,Film)

wontLike(ag2,Film) <- actor(Film,timRobbins), boring(Film)

¬boring(Film) <- actor(Film,morganFreeman), goodUserRating(Film)

Assumptions = {willLike(Ag,Film), boring(Film), goodUserRating(Film)}

Contrary(willLike(Ag,Film)) = wontLike(Ag,Film)

Contrary(boring(Film)) = ¬boring(Film)

Contrary(goodUserRating(Film)) = badUserRating(Film)

Consider two concrete agents, ag1 and ag2, with initial private beliefs as follows:
Priv(ag1) = {criticallyAcclaimed(shawshankRedemption), actor(shawshankRedemption,morganFreeman)}
Priv(ag2) = {actor(shawshankRedemption,timRobbins)}

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39, The Eightfold Way of Deliberation Dialogue

Contents of 'The Eightfold Way of Deliberation Dialogue' (2007), Peter McBurney, David Hitchcock, Simon Parsons

"Deliberation dialogues occur when two or more participants seek to jointly agree on an action or a course of action in some situation..."

1, Introduction

2, Deliberation Dialogues

3, A Formal Model of Deliberations

The following types of sentences are defined: Actions, Goals, Constraints, Perspectives, Facts, Evaluations

The presented formal dialogue model consists of eight stages: Open, Inform, Propose, Consider, Revise, Recommend, Confirm, Close

4, Locutions for a Deliberation Dialogue Protocol

The permissible locutions in the dialogue game are as follows: open_dialogue, enter_dialogue, propose, assert, prefer, ask_justify, move, reject, retract, withdraw_dialogue

5, Example

6, Assessment of the DDF Protocol: Human Dialogues, Deliberation Process, Deliberation Outcomes

7, Discussion: Contribution, Related Work, Future Research

8, Appendix: Axiomatic Semantics