1. EA C461 – Artificial Intelligence Logical Agent
S.P.Vimal

2. To discuss… Propositional Inference in Wumpus World
Circuit Based Agent
Vimal EA C461- Artificial Intelligence

3. Wumpus World Let us look at sentences in the WW- KB
The agent begins its exploration from a square known to be safe
R1: P1,1
R2: W1,1
For every square [x,y], if the agent perceives breeze…
R3 - R18: Bx,y  (Px,y+1  Px,y-1  Px+1,y  Px-1,y)
Vimal EA C461- Artificial Intelligence

4. Wumpus World For every square [x,y], if the agent perceives stench…
R19 – R34: Bx,y  (Px,y+1  Px,y-1  Px+1,y  Px-1,y)
How do we express there is exactly one wumpus
We can represent it 2 sentences
There is at least one wumpus
R35: W1,1  W1,2  …  W4,4
Vimal EA C461- Artificial Intelligence

5. Wumpus World We have used 64 distinct symbols in the KB
For any two squares, one must be wumpus-free
This should be stated for every pair of squares
[n (n-1)] / 2 number of sentences
R36 :W1,1  W1,2
R37 : W1,1  W1,3 …
R155 : _________
We have used 64 distinct symbols in the KB
Vimal EA C461- Artificial Intelligence

6. Wumpus World –Agent Program
Additional Program
Variables
Vimal EA C461- Artificial Intelligence

7. Wumpus World –Agent Program
ASK  Entailment computation
TT-Entails rows-
DPLL / WALKSAT performs better
For a large ww, the number of sentences in the KB will be huge
WE could not capture the property “breeze in a square indicates pit in at least one of directly adjacent square”
Can we keep track of location and orientation within the KB?
Vimal EA C461- Artificial Intelligence

8. Location, Orientation in WW
Can we add propositions like
L1,1 Λ FacingRight Λ Forward  L2,1
KB will entail both L1,1 and L2,1.
How???
What we intended to capture is this
L1,1 (t) Λ FacingRight Λ Forward  L2,1(t+1)
FacingRight Λ TurnLeft (t)  FacingUp(t+1)
For every times steps, one such statements???
Assuming the problem is solvable in 100 time steps  10 thousands of additional sentences
Vimal EA C461- Artificial Intelligence

9. Circuit Based Agents Reflex agent with state
Percepts are inputs to sequential circuit
Network of gates and registers
Output are registers corresponding to actions
Circuits are evaluated in a dataflow model
Value stored at each proposition symbol gives the truth value of the corresponding symbol at the current time t.
Vimal EA C461- Artificial Intelligence

10. Circuit Based Agents
Vimal EA C461- Artificial Intelligence

11. Circuit Based Agents
Vimal EA C461- Artificial Intelligence

12. Circuit Based Agents… Location???
One register for each Lxy.
Agent is in [1,1] at t if
The agent was in [1,1] at t-1 and has no moved, tried but bump
It was at [1,2], facing down and moved forward
It was at [2,1] facing left and move forward
Vimal EA C461- Artificial Intelligence

13. Circuit Based Agents… Location???
Vimal EA C461- Artificial Intelligence

14. Circuit Based Agents… a problem
What will be the initial truth value contained in B4,4
The agent cannot set a truth value for it
Need to represent unknown
Use knowledge propositions K(B4,4) , K(רB4,4)
Vimal EA C461- Artificial Intelligence

15. Inference based agents vs. Circuit based Agents
Declarative vs. Procedural
Conciseness
Computational Efficiency
Completeness
Vimal EA C461- Artificial Intelligence

16. Summary
Logical agents apply inference to a knowledge base to derive new information and make decisions
Basic concepts of logic:
syntax: formal structure of sentences
semantics: truth of sentences wrt models
entailment: necessary truth of one sentence given another
inference: deriving sentences from other sentences
soundness: derivations produce only entailed sentences
completeness: derivations can produce all entailed sentences
Wumpus world requires the ability to represent partial and negated information, reason by cases, etc.
Resolution is complete for propositional logic Forward, backward chaining are linear-time, complete for Horn clauses
Propositional logic lacks expressive power
Vimal EA C461- Artificial Intelligence