Animal intelligence and problem solving Flashcards

1
Q

what do we mean by intelligence?

A

Even in humans it is a debate

Is intelligence one thing – general purpose ability (Spearman’s g)?

Or composite of social skills, verbal skills, spatial skills etc. – and what would this mean as applied to humans

In humans use IQ tests, in animals use variety of diff problems to assess intelligence – look for ev of ability to use rules, reason, as distinct from perf based on associative learning

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2
Q

warning

A

Problems with assessing animal intelligence:
1. Human like behav in animals may appear to be intelligence when not
2. E.g. clever Hans
 Couldn’t answer certain problems when over a loudspeaker
- Looked for people’s expressions – has to be someone in the room that knows the answer

“In no case may we interp an action as the outcome of the exercise of a higher psychical faculty, if it can be interp as the outcome of the ex of one which stands lower in the psych scale”

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3
Q

historical background

A

2 schools of thought

  1. Gradual (quan) diff between humans and other animals
  2. Sharp (qual) distinction between humans and other animals – MacPhail hyp – do diff in way vertebrates learn – might learn at diff rates esp. in diff circumstances – humans can just do more
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4
Q

trial-and-error

A

Thorndike

  • No insight
  • Law of effect
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5
Q

insight

A

• Köhler about Thorndike’s exps (1927)
o “If essential portions of exp apparatus cannot be seen by animals, how can they use intelligence faculties in tackling the situ?
o Setting problem that cannot solve

Gestalt psych

Perception of relations

No PA involved

If too difficult: trial and error

E.g. monkey’s and crates to reach bananas
o Realised problem – discovered solution – then executed solution
o Anecdotal ev – limitation

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6
Q

Epstein et al. (1984)

A
study with birds
o	Plastic banana – peck = grain
o	Cannot reach it
o	Uses block 
o	Took months to train 
o	Not same at all?
o	Proof that animal could learn to do this 

Don’t know what experiences chimp had – boxes always in compound and played with/interacted with them – cannot claim it happened without training

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7
Q

insight (2)

A

Insight learning ev often open to interp

Köhler – anecdotal, no knowledge of prior experience of animals

Epstein – training experience produced intelligent and insightful behav – existence proof

Insight v instrumental learning

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8
Q

spatial intelligence - detour tests

A

Köhler (1925)

Key feature
 Distance of food from (transparent) fence

Poucet (1983): cats – transparent v opaque barriers
- If wants to go towards it = naturally takes In down the longer path
 Opaque = takes shorter path

Some animals able to solve problem by moving away from food to take optimal route to goal

Intelligence? /triumph of instrumental over Pavlovian? – which can be difficult to achieve (e.g. omission schedules)

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9
Q

tool use

A

Use of external object as functional extension to attain immediate goal

Many animals observed engaging in primitive tool use – indicator of intelligence?

Dropping stone on mussel (using tools) v dropping mussel on stone (random behav/chance)

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10
Q

tool use as ev of causal inference - Povinelli (2000)

A

Some animals can learn to push from current side – intelligence?

50/50 which end go for at first

One side more successful than other

Put food at other side of trap – has to push from other end – mostly get it wrong at first

see notes

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11
Q

tool selectivity

A

Chappell and Kacelnik (2002): new Caledonian Crows
o Have to learn to pick right stick length

see notes

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12
Q

tool construction

A

Weir, Chappell and Kacelnik (2002): tool shaping in new Caledonian Crows
o Best ev
o Use handle to pick bucket up

see notes

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13
Q

can animals use rules?

A

Claimed they can – same/diff relation studied using transfer tests in matching to sample studies – successful transfer observed, results explained in terms of discrimination based in estimated of recency/familiarity

Animal has some notion, based on trace strength – how long ago last encountered stim – perceived recency

In matching to sample, of learns to select “most recent one”, show transfer to novel stim

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14
Q

serial reversal learning - Mackintosh (1974)

A

Learn problem to criterion of 90% correct

Then reverses – learn to same criterion again – colour that matters

Reverses again – learn to same criterion etc.

On later reversals, animal makes less errors in acquiring discrimination – in extreme cases just 1 error (chimps) – ev of “win – stay / lose -shift” rule?

see notes

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15
Q

analysis for Mackintosh (1974)

A

Result consistent with idea that something like rule used by animals, but other explanations must be ruled out first

Animal may learn which aspects of stim to attend to – and this enhances learning – but could it lead to one-trial learning?

Most animals don’t just make one error

Gets faster as attends to correct stim quality

Need some form of transfer test

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16
Q

learning sets - Harlow (1949)

A

Learn problem to criterion of 90% correct – object that matters – not position

Then changes – learn to same criterion again

Changes again – learn to same criterion etc.

On later problems, animal makes less errors in acquiring discrimination – in extreme cases just 1 error (chimps) – ev of “win – stay / lose -shift” rule?

see notes

17
Q

Harlow analysis

A

Learning to attend to certain stim features won’t explain results – as stim change from problem to problem – one-trial acquisition of task very suggestive of win-stay/lose-shirt rule use

Could obtaining reinforcer used as cue to solve discrim? – animal might learn that recently seen cue good if just obtained reinforcer, but bad if hasn’t conditional discrim

Know animals can learn blue stim rewarded when tone sounds, but yellow rewarded when clicker sounds – no need to postulate rule use to explain this

18
Q

transitive inference

A

Can perf transitive inference: if A bigger than B, and B bigger than C, is A bigger than C?

Can animals do this> if so – would it be ev for use of relational rule?

Ev for transitive inference in animals, some can be explained in simpler terms but other ev persuasive

Basic design is to train animals on chain of pairwise items – and then test novel pairing

19
Q

McGonigle and Chalmers (1977, 1992) - squirrel monkeys

A

If animals choose B over D – ev of TI?

see notes

20
Q

an associative explanation - von Fersen et al. (1991)

A

A always reinforced, E never is
B, C and D partially reinforced, but B paired with A and so can associatively retrieve it and benefit from A’s strong association with reward
D has similar r’ship to E]B chosen when paired with D

see notes

21
Q

Treichler and Van Tilburg (1996) - rhesus monkeys

A

Attempt to rule out associative explanation that’s not convincing

see notes

22
Q

analogical reasoning

A

Can reason by analogy: puppy is to dog as lamb is to ?

Can animals do this? – if so, would be ev for use of some relational rule (“juvenile form”)

No – one exception – Sarah the chimp

Sarah trained to communicate using symbols, and learned to use symbols for same and diff appropriately

Gillan et al. (1981)
o Sarah able to make right choice – can opener – gets right on first trial