CSE 574: Planning & Learning
Instructor: Dr. Subbarao Kambhampati
Project 1 Submission
Name: Srinivas Vadrevu
Date: 09/23/2004
1. English Description of the Domain:
This domain describes various stages in human life, the incidents he/she goes through, and their
effect on his /her life. The predicates in the domain correspond to various conditions in the
human life, for e.g., whether the person is alive, dead, has college degree, married, broke, or
blissful. The domain also models some material/non-material possessions of the human, for e.g.,
car, home, education, etc. The actions in the domain describe various incidents that happen in
the life of a human, such as graduation, securing a job and getting married. Some of the
problems defined in the domain include transitioning from one stage of the life to another stage.
Since the desired plan is very obvious in these problems, it is interesting to see that the planners
which do not have any prior knowledge of the domain perform according to the expectations.
2. PDDL Description:
;;
;; PDDL file for the domain LIFE
;; created for CSE 574: Planning and Learning Course by Subbarao Kambhampati at ASU
;;
;; Author: Srinivas Vadrevu 09/21/2004
;;
;; Disclaimer: The conditions, situations expressed in this domain and
;; problems are fictious and have no resemblence to any particular person.
;; Any similarity to actual persons living or dead is unintentional
;; and purely coincidental. This domain and problems do not reflect the thoughts
;; or opinions of my company, my university, my colleagues, my parents,
;; my significant other, my friends, my worst enemies, or me; don't quote
;; me on that; don't quote me on anything, except that what I say is OK.
(define (domain life)
(:requirements :adl :typing :conditional-effects)
(:types degree job academicarea place university name car)
(:predicates
(rich ?n1 -name)
(child ?n1 - name)
(young ?n1 - name)
(old ?n1 - name)
(has-job ?n1 - name ?j1 - job)
(no-college-degree ?n1 - name)
(single ?n1 - name)
(studies-in ?n1 - name ?d1 - degree ?a1 - academicarea ?u1 - university ?p1 - place)
(has-degree ?n1 - name ?d1 - degree ?a1 - academicarea ?u1 - university ?p1 - place)
(broke ?n1 - name)
(married ?n1 - name ?n2 - name)
(divorced ?n1 - name)
(retired ?n1 - name)
(resides-in ?n1 - name ?p1 - place)
(has-car ?n1 - name ?c1 - car)
(has-house ?n1 - name ?p1 - place)
(yogi ?n1 - name)
(blissful ?n1 - name)
(alive ?n1 - name)
(drug-addict ?n1 - name)
1
(intelligent ?n1 - name)
(loser ?n1 - name)
(successful ?n1 - name)
(loyal ?n1 - name)
(like ?n1 - name ?n2 - name)
)
(:action graduate
:parameters
(?n1 - name ?u1 - university ?d1 - degree ?a1 - academicarea ?p1 - place)
:precondition
(and
(no-college-degree ?n1)
(resides-in ?n1 ?p1)
(studies-in ?n1 ?d1 ?a1 ?u1 ?p1)
(not (drug-addict ?n1))
)
:effect
(has-degree ?n1 ?d1 ?a1 ?u1 ?p1)
)
(:action dropout
:parameters
(?n1 - name ?u1 - university ?d1 - degree ?a1 - academicarea ?p1 - place)
:precondition
(and
(no-college-degree ?n1)
(resides-in ?n1 ?p1)
(studies-in ?n1 ?d1 ?a1 ?u1 ?p1)
(drug-addict ?n1)
)
:effect
(and
(not (studies-in ?n1 ?d1 ?a1 ?u1 ?p1))
(broke ?n1)
)
)
(:action marry
:parameters (?n1 - name ?n2 - name)
:precondition
(or
(and
(single ?n1)
(single ?n2)
(like ?n1 ?n2))
(divorced ?n1)
(divorced ?n2)
)
:effect
(and
(married ?n1 ?n2)
(not (single ?n1))
(not (single ?n2))
(not (blissful ?n1))
(not (blissful ?n2))
)
)
(:action become-unloyal
:parameters (?n1 - name)
:precondition (alive ?n1)
:effect (not (loyal ?n1))
)
(:action divorce
:parameters (?n1 - name ?n2 - name)
:precondition
(and
(married ?n1 ?n2)
2
(or
(not (loyal ?n1))
(not (loyal ?n2))
)
)
:effect
(and
(divorced ?n1)
(divorced ?n2)
)
)
(:action get-job
:parameters (?n1 - name ?j1 - job ?a1 - academicarea ?d1 - degree ?u1 - university ?p1 - place ?c1 - car)
:precondition
(and
(has-degree ?n1 ?d1 ?a1 ?u1 ?p1)
(intelligent ?n1)
)
:effect
(and
(has-job ?n1 ?j1)
(not (broke ?n1))
(rich ?n1)
(has-car ?n1 ?c1)
)
)
(:action born
:parameters (?n1 - name)
:precondition (not (alive ?n1))
:effect
(and
(alive ?n1)
(blissful ?n1)
)
)
(:action car-accident
:parameters (?n1 - name ?c1 - car)
:precondition
(and
(alive ?n1)
(has-car ?n1 ?c1)
(drug-addict ?n1)
)
:effect (not (alive ?n1))
)
(:action is-a-loser
:parameters (?n1 - name ?d1 - degree ?p1 - place ?c1 - car ?j1 - job ?a1 - academicarea ?u1 - university)
:precondition (alive ?n1)
:effect
(when (and
(broke ?n1)
(no-college-degree ?n1)
(not (has-job ?n1 ?j1))
(not (has-house ?n1 ?p1))
(not (has-car ?n1 ?c1)))
(loser ?n1))
)
(:action is-successful
:parameters (?n1 - name ?d1 - degree ?p1 - place ?c1 - car ?j1 - job ?a1 - academicarea ?u1 - university)
:precondition (alive ?n1)
:effect
(when (and
(has-job ?n1 ?j1)
(has-house ?n1 ?p1)
(has-car ?n1 ?c1)
3
(has-degree ?n1 ?d1 ?a1 ?u1 ?p1)
(rich ?n1))
(successful ?n1))
)
(:action domain-axioms
:parameters (?n1 - name ?p1 - place)
:precondition: (alive ?n1)
:effect
(and
(when (rich ?n1)
(has-house ?n1 ?p1))
(when (yogi ?n1)
(blissful ?n1))
)
)
(:action fired
:parameters (?n1 - name ?j1 - job ?p1 - place ?c1 - car)
:precondition (has-job ?n1 ?j1)
:effect
(and
(not (has-job ?n1 ?j1))
(broke ?n1)
(not (has-car ?n1 ?c1))
(not (has-house ?n1 ?p1))
)
)
)
3. Issues in Modeling the Domain:
Numerical Predicates & Categorization:
The domain requires a numerical attribute for some of the predicates, such as money in dollars,
age, etc. I initially modeled these predicates as numerical attributes, but I quickly realized that I
have to manipulate with numerical comparison methods such as greater than, less than in my
actions which increases the complexity of simpler actions. In some cases, the boundaries (the
amount of the money, or the age of the person) are not very clear, and it is not appropriate to
have hard boundaries on these attributes. So I decided to abstract these predicates into
categories, such as rich, poor, young, old, etc.
Domain Axioms:
The domain requires some axioms that will help the planner to prune the search space and to
reach to the goal quickly. These axioms are so obvious that it is very common to ignore these
and let the planner decide what is best. Even though there is support for domain axioms in
PDDL, I realized that these axioms can be modeled as special actions that do not require any
preconditions and have conditional effects. This way, I can group the domain axioms into
categories, such as personal related, job related, and general facts.
Miscellaneous:
After I modeled the domain and started modeling various problems in the domain, I realized that
many predicates that I have in the domain are redundant. For example, (alive ?n1) and (dead
?n1) are both redundant and one of them suffices the purpose. I had to convert some of the
predicates into actions because there is no way to make such predicates true without creating an
action, for e.g., I initially had a predicate (college-dropout ?n1), but then I realized that is
actually an action and not a predicate and created an action that gives (no-college-degree ?n1)
as an effect.
Conditional Effects:
4
I observed that when the planner has opportunity to use actions without conditional effects, it
uses them instead of the ones with conditional effects. I had a conditional effect, which given
when a person is young or old or child implies that the person is alive (domain axiom). Now
when I check if the person is alive, it executes the born action, instead of this action with
conditional effect. This is quite interesting to see. Since it is awkward to see the planner
executing the born action when the person is young, I removed the conditional effect and
included the ‘alive’ predicate in my initial state.
Negative Literals in Initial State:
I could not use negative literals as facts in the initial state in ADL description, so I had to
introduce an action that negates the literals that I wanted to get around it. I am sure there is an
easier way to resolve this issue but I could not find any obvious solutions.
4. Planning Problems from the Domain
Problem 1 (Successful):
;;
;; PDDL file for Problem 01 in Life Domain
;; created for CSE 574: Planning and Learning Course by Subbarao Kambhampati at ASU
;;
;; Author: Srinivas Vadrevu 09/21/2004
;;
(define (problem P01_Successful)
(:domain life)
(:objects
Virinchi - name
IIM - university
Ahmedabad - place
Finance - academicarea
Jaguar - car
MBA - degree
Accountant - job
)
(:init
(alive Virinchi)
(intelligent Virinchi)
(no-college-degree Virinchi)
(resides-in Virinchi Ahmedabad)
(studies-in Virinchi MBA Finance IIM Ahmedabad)
)
(:goal
(and
;(has-degree Virinchi MBA Finance IIM Ahmedabad)
;(has-job Virinchi Accountant)
;(has-house Virinchi Ahmedabad)
(successful Virinchi)
)
)
)
Problem 2 (NotSuccessful):
;;
;; PDDL file for Problem 02 in Life Domain
;; created for CSE 574: Planning and Learning Course by Subbarao Kambhampati at ASU
;;
5
;; Author: Srinivas Vadrevu 09/21/2004
;;
(define (problem P02_NotSuccessful)
(:domain life)
(:objects
Joe - name
IIM - university
Ahmedabad - place
Finance - academicarea
Jaguar - car
MBA - degree
Accountant - job
)
(:init
(alive Joe)
(drug-addict Joe)
(no-college-degree Joe)
(resides-in Joe Ahmedabad)
(studies-in Joe MBA Finance IIM Ahmedabad)
)
(:goal (successful Joe))
)
Problem 3 (Loser):
;;
;; PDDL file for Problem 03 in Life Domain
;; created for CSE 574: Planning and Learning Course by Subbarao Kambhampati at ASU
;;
;; Author: Srinivas Vadrevu 09/21/2004
;;
(define (problem P03_Loser)
(:domain life)
(:objects
Joe - name
IIM - university
Ahmedabad - place
Finance - academicarea
Jaguar - car
MBA - degree
Accountant - job
)
(:init
(alive Joe)
(drug-addict Joe)
(no-college-degree Joe)
(resides-in Joe Ahmedabad)
(studies-in Joe MBA Finance IIM Ahmedabad)
)
(:goal
(and
;(broke Joe)
;(has-degree Joe MBA Finance IIM Ahmedabad)
(loser Joe)
)
6
)
)
Problem 4 (Marriage):
;;
;; PDDL file for Problem 04 in Life Domain
;; created for CSE 574: Planning and Learning Course by Subbarao Kambhampati at ASU
;;
;; Author: Srinivas Vadrevu 09/21/2004
;;
(define (problem P04_Marriage)
(:domain life)
(:objects
Ahalya - name
Gautam - name
Indra - name
Pushpak - car
Rishi - degree
Veda - academicarea
Ashram - university
King - job
Swarga - place
)
(:init
(alive Gautam)
(alive Indra)
(alive Ahalya)
(single Indra)
(single Ahalya)
(single Gautam)
(like Gautam Ahalya)
)
(:goal
(and
(divorced Gautam)
(married Indra Ahalya)
)
)
)
Problem 5 (Reincarnation):
;;
;; PDDL file for Problem 05 in Life Domain
;; created for CSE 574: Planning and Learning Course by Subbarao Kambhampati at ASU
;;
;; Author: Srinivas Vadrevu 09/21/2004
;;
(define (problem P05_Reincarnation)
(:domain life)
(:objects
Ravan - name
Mandodari - name
Pushpak - car
7
VedaExpert - degree
Veda - academicarea
Anthapuram - university
King - job
Lanka - place
)
(:init
(alive Ravan)
(alive Mandodari)
(drug-addict Ravan)
(no-college-degree Ravan)
(married Ravan Mandodari)
(resides-in Ravan Lanka)
(has-car Ravan Pushpak)
(studies-in Ravan VedaExpert Veda Anthapuram Lanka)
)
(:goal (blissful Ravan))
)
5. Results From FF
AltAlt planner had some problems parsing my domain and problem files. So I used FF which
gave solutions to all the problems in a way I thought it should. It’s PDDL syntax checker was
very helpful in correcting my PDDL files. These are the results obtained by running FF planner on
my domain and the above 5 problems.
Problem 1 (Successful):
! general > ffunix -p ../Domains/Life/ -o LifeDomain.PDDL -f P01_Successful.PDDL
ff: parsing domain file
domain 'LIFE' defined
... done.
ff: parsing problem file
problem 'P01_SUCCESSFUL' defined
... done.
Cueing down from goal distance:
4 into depth [1]
3
[1]
2
[1]
1
[1]
0
ff: found legal plan as follows
step
0:
1:
2:
3:
GRADUATE JOE IIM MBA FINANCE AHMEDABAD
GET-JOB JOE ACCOUNTANT FINANCE MBA IIM AHMEDABAD JAGUAR
DOMAIN-AXIOMS JOE AHMEDABAD
IS-SUCCESSFUL JOE MBA AHMEDABAD JAGUAR ACCOUNTANT FINANCE IIM
time spent:
0.01
0.01
0.00
0.00
0.00
0.02
seconds
seconds
seconds
seconds
seconds
seconds
instantiating 8 easy, 0 hard action templates
reachability analysis, yielding 13 facts and 7 actions
creating final representation with 11 relevant facts
building connectivity graph
searching, evaluating 5 states, to a max depth of 1
total time
Problem 2 (NotSuccessful):
! general > ffunix -p ../Domains/Life/ -o LifeDomain.PDDL -f P02_NotSuccessful.PDDL
ff: parsing domain file
domain 'LIFE' defined
8
... done.
ff: parsing problem file
problem 'P02_NOTSUCCESSFUL' defined
... done.
Enforced Hill-climbing failed !
switching to Best-first Search now.
best first search space empty! problem proven unsolvable.
time spent:
0.01
0.01
0.00
0.00
0.00
0.02
seconds
seconds
seconds
seconds
seconds
seconds
instantiating 8 easy, 0 hard action templates
reachability analysis, yielding 9 facts and 5 actions
creating final representation with 6 relevant facts
building connectivity graph
searching, evaluating 2 states, to a max depth of 0
total time
Problem 3 (Loser):
! general > ffunix -p ../Domains/Life/ -o LifeDomain.PDDL -f P03_Loser.PDDL
ff: parsing domain file
domain 'LIFE' defined
... done.
ff: parsing problem file
problem 'P03_LOSER' defined
... done.
Cueing down from goal distance:
2 into depth [1]
1
[1]
0
ff: found legal plan as follows
step
0: DROPOUT JOE IIM MBA FINANCE AHMEDABAD
1: IS-A-LOSER JOE MBA AHMEDABAD JAGUAR ACCOUNTANT FINANCE IIM
time spent:
0.01
0.01
0.00
0.00
0.00
0.02
seconds
seconds
seconds
seconds
seconds
seconds
instantiating 8 easy, 0 hard action templates
reachability analysis, yielding 9 facts and 5 actions
creating final representation with 6 relevant facts
building connectivity graph
searching, evaluating 3 states, to a max depth of 1
total time
Problem 4 (Marriage):
! general > ffunix -p ../Domains/Life/ -o LifeDomain.PDDL -f P04_Marriage.PDDL
ff: parsing domain file
domain 'LIFE' defined
... done.
ff: parsing problem file
problem 'P04_MARRIAGE' defined
... done.
Cueing down from goal distance:
3 into depth [1]
2
[1]
1
[1]
0
ff: found legal plan as follows
step
0: MARRY GAUTAM AHALYA
1: DIVORCE GAUTAM AHALYA
2: MARRY INDRA AHALYA
time spent:
0.02 seconds instantiating 37 easy, 0 hard action templates
0.03 seconds reachability analysis, yielding 21 facts and 31 actions
0.00 seconds creating final representation with 18 relevant facts
9
0.00 seconds building connectivity graph
0.00 seconds searching, evaluating 4 states, to a max depth of 1
0.05 seconds total time
Problem 5 (Reincarnation):
! general > ffunix -p ../Domains/Life/ -o LifeDomain.PDDL -f P05_Reincarnation.PDDL
ff: parsing domain file
domain 'LIFE' defined
... done.
ff: parsing problem file
problem 'P05_REINCARNATION' defined
... done.
Cueing down from goal distance:
2 into depth [1]
1
[1]
0
ff: found legal plan as follows
step
0: CAR-ACCIDENT RAVAN PUSHPAK
1: BORN RAVAN
time spent:
0.01
0.02
0.00
0.00
0.00
0.03
seconds
seconds
seconds
seconds
seconds
seconds
instantiating 20 easy, 0 hard action templates
reachability analysis, yielding 22 facts and 17 actions
creating final representation with 16 relevant facts
building connectivity graph
searching, evaluating 3 states, to a max depth of 1
total time
6. Discussion on Results:
It is interesting to see that the results obtained by FF planner matched exactly with my intuition
of the problems. Even though the domain is large, the problems were quite simple and it was
easy to verify the solutions given by FF. The maximum length of the plan for all the problems is
3. There is one problem (Problem 3) for which FF could not give the solution, where the answer
is intuitively false but there is no way for the learner to figure that out. The enforced hillclimbing algorithm could not yield any solutions for this problem. This illustrates and enforces
the point that knowledge representation is an important issue in modeling the domains. I
personally felt PDDL is not the best language to model planning domains and problems as I was
not able to represent many things I wanted in a simpler way. These issues were outlined in
Section 3.
7. Comparison of My Domain with Other Domains
Most of the domains we considered in the previous project are much complex than my artificial
domain. The problems were harder to solve and some of the planners took long time to solve
the problems. The average length of the plan was also much higher. Even though the ‘life’
domain is complex enough, the problems were not very hard for the planner to solve and it
found solutions within reasonable amount of time. In total, this exercise was helpful in
understanding the modeling issues of a domain and gave some insight into the workings of a
general planner.
10