Nicole J. Saam and Andreas Harrer (1999)
Journal of Artificial Societies and Social Simulation vol. 2, no. 1, <http://jasss.soc.surrey.ac.uk/2/1/2.html>
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Received: 25-Nov-98 Accepted: 20-Dec-99 Published: 31-Jan-99
|Table 1: Alternative representations of norms inside the agents' architectures (norm-abiding systems)|
|Norms as||built-in constraints:|
norms are seen as constraints on the agents' action repertoires (behavioural notion); no truly normative choice
|build-in ends (goals):|
cognitive agents are allowed to choose among competing goals (instead of simply applying procedures and routines) but they treat norms like any other of their goals
explicit and specific mental object; differs from a constraint since it does not automatically reduce the set of actions available to the agents; and from a goal since it is not immediately transformed into a goal
|reliability||high reliability: the constraints will always be executed||low reliability: goals may be abandoned when they clash with competing, more urgent needs||average reliability: agents may give up normative goals, but this will cost them more than abondoning ordinary goals|
|learning||no learning: new constraints are implemented when the system is off-line||average learning: build-in ends should be added when the system is off-line;||normative goals are autonomously produced on the grounds of normative beliefs, and in principle beliefs may be acquired when the system is on-line|
|novelty||no novelty: constraints reduce available actions; only proscriptions, that is, prohibitions ('Don't ...'), can be represented, but not prescriptions ('Do...')||build-in ends may correspond to prescriptions and not only to prohibitions; but since learning is not granted, there ought to be a one-to-one correspondence between social norms and internal goals with a consequent high computational complexity||normative beliefs may be formulated as prescriptions, and not as mere prohibitions|
|repair||no repair: agents are not endowed with the capacity for modifying unsuccessful constraints||goal-oriented systems ought to be able to try out several solutions and choose those that achieve their goals to the highest degree, before giving up their goals||as with any other kind of goal, plans for normative goals are subject to change and repair|
|social control||no need||no social control: agents may have preferences corresponding to norms or not; they may cling to these or abandon them as a function of circumstances||since normative goals are a special type of goals, and normative actions have specific costs, agents can be shown to be interested in some monitoring of norms|
actions prescribed are in the interests of a subset of the MAS at the expense of the rest; these are either the norms aimed to restore equity, protecting the interests of underprevileged categories, or, conversely, norms which favour inequality, protecting the interests of the privileged party (e.g. norms defending private property); (Conte and Castelfranchi 1995b: 115f).The concept of partial tutoriality seems to be derived from Ullman-Margalit's 'norms of partiality'. It is complemented by distributive tutoriality (actions prescribed are in the interests of all members of the system) and collective tutoriality (actions prescribed are in the interest of the MAS as a collective, but independent of and outside the interest of its members). Do norms have a function in relation to (in)equality? Remember Ullman-Margalit's third argument: Norms are solutions to problems of inequality.
|Table 2: Types of actions in the Conte and Castelfranchi model|
|Action type||Order of preference among these actions||Cost of action (in food items)|
|Table 3: The results of the Castelfranci and Conte model|
Source: from JASSS Volume 1, Issue 3, http://jasss.soc.surrey.ac.uk/1/3/3.html
|Table 4: Replication results|
|Table 5: Private property and equal heritage (alphai = alphaj = 0.5)|
|Table 6: Private property and unequal heritage (alphai = 0.9, alphaj = 0.1)|
|vt = 20 + beta (st-1 - 40)||(1)|
|Table 7: Unequal renewal of resources (beta = 0.2)|
|Table 8: Unequal renewal of resources (beta = 10.0)|
|Table 9: Unequal renewal of resources (beta = 0.0375), time restriction removed|
|vt = 20 + pt-1||(2)|
|Table 10: Normative behavior from a sociological point of view; two sub-populations: Blind vs Normative (50:50)|
|Table 11: Normative behavior from a sociological point of view; two sub-populations: Strategic vs Normative (50:50)|
Key to tables 10 and 11:
The results are gathered from sets of 100 matches for each Strategy. The values shown are from left to right: The average of the agent's strength (Str) at the end of the match, the standard deviation of Str, the average of the standard deviation (St. Dev) of the agents' strength values at the end of the match, the standard deviation of St. Dev, the average number of aggressions (Agg) occuring during one match, the standard deviation of Agg, the average value of power (Pow) and the standard deviation of Pow.
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