Dynamics of Trust - Trust Theory: A Socio-Cognitive and Computational Model - page 174

τ Ξ

τ

τ

Figure 6.14 Generalization in case Ag X knows only the trustee's features. (Reproduced with kind
permission of Springer Science+Business Media C

2008)

inferential reasoning on the match between properties and the features). In more formal terms:

c1) Trust Ag X ( Ag Y ,τ )

c2) Bel Ag X ( f AgY ≡{ f 1 ,..., f n } )

p 1 ,..., p k }∪{ c3) ¬ Bel Ag X ( τ ≡{ p 1 ,..., p m } )

's features ( c3 ), Ag X can believe that a different (but in some
way analogous) agent Ag Z is trustworthy on the task

Despite the ignorance about τ

(generalization of the agent) just starting
from the previous cognitive elements ( c1 and c2 ) and from the knowledge of Ag Z 's features.
He can evaluate the overlap among the features of Ag Y and Ag Z and decide if and when to trust
Ag Z on

τ

. While, in this case, it is not possible to generalize a task because there is no way of
evaluating any analogies with other tasks.
So we can conclude (Figure 6.15) that in the case ( C ) agent generalization is possible: in
fact the set (c1, c2, c3) permits agent generalizations but does not permit task generalizations .
Exactly as in case B , also in this case we could imagine an indirect task generalization. If
Ag X trusts a set of different but similar agents AG1

τ

≡ { Ag Y ,Ag W ... ,Ag Z } (he can evaluate this

τ Ξ

No Generalization
on tasks

Ξ

Ag Y

AG X

AG X

Generalization
on agents

Trust (AgY, τ )

Trust (Ag Z , τ )

AgX

AgX

Figure 6.15 Generalization in case Ag X knows only the task's properties. (Reproduced with kind
permission of Springer Science+Business Media C 2008)