Transcript A Computer Aided Instruction System for the International

A Computer Aided Instruction System
for the International Law CISG
Kaoru Hirota
Dept.of Computational Intelligence
& Systems Science
Tokyo Institute of Technology
[email protected]
“Legal Expert Systems” project
1992-1998 1999-2001
Japanese Ministry of Education, Science
and Culture
30 lawyers and computer scientists
Hajime YOSHINO （Meiji Gakuin Univ.)
Kaoru HIROTA (Tokyo Institute of
Technology)
CISG: United Nation Convention on Contracts
for the International Sale of Goods
Japanese / English versions
Background
Target Law
United Nation Convention on Contract for the
International Sale of Goods: CISG
Cases
Case Law on UNCITL(United Nations
Commission on International Trade law)
Texts: CLOUT
Background
Vagueness in Legal Concept
CISG Article 14-1
A proposal for concluding a contract addressed to one
or more specific persons constitutes an offer if
it is sufficiently definite and indicates the intention of
the offer to be bound in case of acceptance.
A proposal is sufficiently definite if it indicates the
goods and expressly or implicitly fixes or makes
provision for determining the quantity and the price.
Case Based Reasoning
Legal Case Based Reasoning
ISSUE: α
Fuzziness
a : Event of Precedent
a' ： Event of Query Case
Precedent : A(a) Conclusion: B(a)
Query case :A' (a')
If A(a) and A' are similar:
Matching
A(a) ≒ A' (a')
The Conclusion of A' is the same as A’s
B' (a') ≒ B(a)
Overview of Fuzzy Legal Case
Based Reasoning System
Input
Output
Ｕ
ｓ
ｅ
ｒ
Ｉ
ｎ
ｔ
ｅ
ｒ
ｆ
ａ
ｃ
ｅ
Retrieval
CISG
Case Base
Inference
Explanation-based Representation
Issue : Vague Legal Concept
Feature : The Surface Properties of the Precedent
<Attribute1 : Value1> …..
Case Rule : The Deep properties that describe
relation between legal judgement
and the facts
If fact1 is action1 then ...
Cases Representation (CPF)
Case 1: (Issue 1)
:
(Feature 1)
:
(Case Rule 1)
:
(Issue 2)
:
:
(Issue n)
:
Case i: ( )
:
:
Case n: (
)
:
case4 :
(Malev)
( (issue 41)
14 (1) (No)
(feature 41)
% It fixes the goods
‘ fix1’(‘fix1_c_n1_1’, [
agt: ‘Malev_proposal’,
imp: ‘letter’,
obj: ‘engine_system’,
] ).
% It fixes the quantity
:
:
(case rule 41)
% The whole price is not fixed
:
:
Similarity in legal Retrieval
Logical Product
Precedent
Case(P)
Goods
Quantity
Price
Proposal
Weights Average
Acceptance
Feature
…
Case
…
Query
Case(Q)
S(P,Q)
Similarity
Similarity
Between Issues Between Cases
Two-stages Fuzzy retrieval
Input
First stage:
Retrieving a set of
cases that have the
same issues
Second Stages:
Retrieving the similar
case that has the most
high similarity degree
First Stage
Case Base
Second
Retrieved
Stage
Cases in
First stage
Output
Similarity of Fuzzy Sets Based on
Hausdroff Distance
µ(v)
)B ,A ( H1 d
1.0
A
B
0.0
1.0
v
0
H
)B ,A ( d
① dH (A,B,β) = β *
0
d
(A,B)
H
+ (1- β) *
(A,B)
d H1
② d H0 (A,B) = (inf{r;A0  U (B0 ; r)} + inf {r; B0  U(A0 ; r)} / 2
③ d H1 (A,B) = (inf{r;A1 U (B1; r)} + inf {r; B1  U (A1; r)} / 2
Implementation of Fuzzy
Legal CBR System
Reference Case:
Cultivator
Precedent Cases
Test-Tubes(CLOUT)
Screws(CLOUT)
Chinchilla pelts(CLOUT)
Jet Engine System(CLOUT)
Automobile (CLOUT)
Shoes(CLOUT)
Tire(CLOUT)
Electronic(CLOUT)
Reference Case: Cultivator
Event: proposal
The goods are a cultivator.
The quantity of the cultivator is one.
Concerning the price.
The price of the tractor is fixed.
The machine contains the tractor and rake
Precedent Case: Jet Engine System
Event: Proposal
The goods are jet engine systems.
The quantity of engine systems can be calculated by the quantity of
plans that will be purchased.
Concerning the price:
There is no description about the prices of jet engine systems. The
price of Boeing jet engine is fixed.
The jet engine system includes a support package, services so on.
An Example
Reference Case: Cultivator
Precedent Case
First Stage
Second Stage
Test-Tubes
×
--
Screws
○
0.25
Chinchilla pelts
Jet Engine System
Automobile
Shoes
○
○
×
×
0.25
0.75
---
Tire
×
--
Electronic
×
--
Selected Publications
Journal
1. Kaoru HIROTA, Hajime YOSHINO, MingQiang XU et al: “An Application of Fuzzy Theory to the CaseBased Reasoning of the CISG”,Journal of Advanced Computational Intelligence, Vol.1 No.2 1997, pp.86-93
2. MingQiang XU, Kaoru HIROTA, Hajime YOSHINO: “ A Fuzzy Theoretical Approach to Representation
and Inference of Case in CISG”, International Journal of Artificial Intelligence and Law, Vol.7 No.2-3 1999
pp. 259-272
Conference
1. Hajime YOSHINO, MingQiang XU, Kaoru HIROTA: “A Fuzzy Judgement Approach to Inference of Cases
in CISG”, The Sixth International Conference on Artificial Intelligence and Law, Poster Proceeding, pp. 6064，1997. 6，Australia
2. Hajime YOSHINO, MingQiang XU, Kaoru HIROTA: “Representation and Inference of Case with Fuzziness
in the CISG”, Proc. of the Fourth International Workshop on a Legal Expert System for the CISG, pp. 5-9,
1997. 6, Australia
3. MingQiang XU, Kaoru HIROTA, Hajime YOSHINO: ”Learning Vague Concepts and Making Argument
from Examples by Fuzzy Factors in Interpretive Knowledge-Based System”, The Fifth International
Conference on Soft Computing and Information/Intelligence Systems, pp.191-194，1998. 10, Iizuka, Japan