1. Sense-making software for crime investigation: how to combine stories and arguments? Henry Prakken (& Floris Bex, Susan van den Braak, Herre van Oostendorp, Bart Verheij, Gerard Vreeswijk)

2. Contents A research project: Building software that supports crime investigators Investigate theoretical basis Stories and causality in evidential reasoning Abduction Reasoning with testimonies: Argumentation Combining stories and testimonies: abduction + argumentation

3. The intended software: a sense-making system No knowledge inside, but Supports human users in structuring and visualising their thinking Can calculate with these structures Can link them with case files Should be based on an account of evidentiary reasoning that is: Prescriptive (supporting rational thinking) Natural (close to the way crime investigators think)

4. Stories involve causation Stories are (at least) a sequence of events on a timeline Events are supposedly caused by earlier events Physical causation Mental causation Reasoning with causal information: Prediction: assume or observe event, predict what will happen next Explanation: observe event, explain what could have caused it

5. Example: the King case (1) Fact: King was beaten up by mr. Zomerdijk in backyard of Zomerdijk’s house Prosecution’s story King (a convicted thief) was up to no good King climbs into backyard of Zomerdijk family King enters bedroom King steps on toy Mr. Zomerdijk hears sound Mr. Zomerdijk goes to bedroom King closes door and runs away

6. Example: the King case (2) Fact: King was beaten up by mr. Zomerdijk in backyard of Zomerdijk’s house Defence’s story King climbs into backyard of Zomerdijk family Wind opens bedroom door Wind hits toy Mr. Zomerdijk hears sound Mr. Zomerdijk goes to bedroom Mr. Zomerdijk sees King in backyard

7. Explanations as causal networks of events Toy makes a sound Observations The door is closed

8. Explanations as causal networks of events Toy makes a sound Observations The door is closed King enters house King steps on toy King closes door

9. Explanations as causal networks of events Toy makes a sound Observations The door is closed King enters house King steps on toy King closes door The wind hits the toy The wind closes the door The wind opens the door Loud bang

10. Explanations as causal networks of events Toy makes a sound Observations The door is closed King enters house King steps on toy King closes door No loud bang was heard The wind hits the toy The wind closes the door The wind opens the door Loud bang

11. A problem(?): testimonies must also be explained King enters house King steps on toy Toy makes a sound Observations The door is closed King closes door Witness wants to protect himself Witness Z often imagines sounds Witness Z says “I heard a sound” Witness Z says “the door was closed”

12. Testimony principle is not a causal but an evidential rule Testimony principle not represented from cause to effect: but from effect to cause: Truth of P is the usual cause of “P”. Other causes of are exceptions. Reasoning is then modelled as constructing and comparing (defeasible) arguments Witness says “P” => P P => Witness says “P”

13. Combining abduction and argumentation Toy makes a sound ‘Observations’ The door is closed King enters house King steps on toy King closes door Witness Z says “I heard a sound” Witness Z is not sincere Witness wants to protect himself Further evidence needed!

14. Conclusion Combining abduction for representing stories and argumentation for reasoning about sources of evidence arguably is natural can arguably be given a sound rational basis But all this should be further investigated