1. Title: Moral Reasoner Domain

2. Sources:
   (a) Creator: T.R. Shultz & J.M. Daley 
   (a) Donors: James L. Wogulis 
               University of California, Irvine
               Irvine, CA USA
   (b) Date:   June 1994

3. Past Usage:

   Darley, J.M. & Shultz, T.R. (1990). Moral rules: Their content and 
   acquisition.  Annual Review of Psychology, 41, 525-556.

   Shultz, T.R. (1990). A rule base model of judging harm-doing. In 
   Proceedings of the Twelfth Annual Conference of the Cognitive 
   Science Society, (pp. 229-236).,Cambridge, MA. Lawrence Erlbaum.

   Wogulis, J.L. (1994). An Approach to Repairing and Evaluating First-Order 
   Theories Containing Multiple Concepts and Negation. Doctoral Dissertation. 
   University of California, Irvine.

4. Relevant Information:

   This is a rule-based model that qualitatively simulates moral reasoning.
   The model was intended to simulate how an ordinary person, down to about
   age five, reasons about harm-doing.

   The horn-clause theory and the 202 instances are the same as were used 
   in (Wogulis, 1994).  The top-level predicate to predict is guilty/1.
   For more information, e.g. on the generation of instances, see 
   (Wogulis, 1994).

5. Target Relation:

   - guilty(case)

   - Number of positive instances: 102

   - Negative instances correspond to the term: 

       - not(guilty(case)).

       - Number of negative instances: 100
  

6. Auxiliary Relations:

   sufficient_for_harm(case,{y,n}).
   produce_harm(case,{y,n}).
   plan_known(case,{y,n}).
   plan_include_harm(case,{y,n}).
   someone_else_cause_harm(case,{y,n}).
   outrank_perpetrator(case,{y,n}).
   monitor(case,{y,n}).
   harm_caused_as_planned(case,{y,n}).
   goal_outweigh_harm(case,{y,n}).
   goal_achieveable_less_harmful(case,{y,n}).
   foresee_intervention(case,{y,n}).
   external_cause(case,{y,n}).
   control_perpetrator(case,{y,n}).
   benefit_protagonist(case,{y,n}).
   careful(case,{y,n}).
   benefit_victim(case,number).
   severity_harm(case,number).
   achieve_goal(case,{y,n}).
   intervening_contribution(case,{y,n}).
   foreseeability(case,{high,low,n}).
   external_force(case,{y,n}).
   mental_state(case,{negligent,reckless,intend,neither}).
   necessary_for_harm(case,{y,n}).