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The input to an agent program is the same as the input to the agent function. Otrue false The Sense - Think - Act cycle

The input to an agent program is the same as the input to the agent function. Otrue false
The "Sense-Think-Act" cycle is fundamental to the "classical paradigm" of AI. Otrue false
Human expertise cannot be adequately modeled as a set of rules. Otrue Ofalse
Complete Agents exploit their body properties to keep the computational load on their brain
low. Otrue Ofalse
Intelligence requires a body, e.g., if the material properties of an agent's muscle-tendon
system is exploited, rapid locomotion is easily achieved. Otrue false
Systems that are not embodied suffer from the symbol-grounding problem, because there is
always a human interpreter in the loop. Otrue false
Bi-pedal walking for robots is possible without computer control. Otrue Ofalse
Embodiment is prerequisite for any kind of intelligence. Otrue false
Language is a good example for "scaffolding". Otrue Ofalse
Deep neural networks are omniscience except for challenging from interpretability.
Otrue O false
Uniform-cost search is a special case of A** search. Otrue false
Depth-first search is a special case of best-first tree search. Otrue Ofalse
h(n)=0 is an admissible heuristic for the 8-puzzle. Otrue false
Q-learning is one typical deep reinforcement learning. Otrue false
The frame of reference problem states that an observer should be careful when deducing
internal mechanisms from external behavior. Otrue Ofalse
In the real world, in contrast to virtual ones, there is always a higher level of uncertainty
present. Otrue false
The "dualist view" has created the "mind-body problem" which is essentially about the
relation between the mind and the body, in particular the brain. Otrue O false
Chess programs have been so successful because in the game of chess there are only few
possible states. Otrue Ofalse
AlphaGo by Google as an AI robot has passed the famous Turing Test. Otrue Ofalse
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