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What (who) is stochastically greater - definition

SOLUTION CONCEPT IN GAME THEORY

Stochastically stable

Greater tubercle

BONY PROJECTION ON THE PROXIMAL END OF THE HUMERUS

Greater tubercle of the humerus; Greater tuberosity; Greater Tubercle; Greater tubercle of humerus; Tuberculum majus; Tuberculum majus humeri; Greater tubercles; Tuberositas major; Major tubercle

The greater tubercle of the humerus is the outward part the upper end of that bone, adjacent to the large rounded prominence of the humerus head. It provides attachment points for the supraspinatus, infraspinatus, and teres minor muscles, three of the four muscles of the rotator cuff, a muscle group that stabilizes the shoulder joint.

https://en.wikipedia.org/wiki/Greater_tubercle

City of Greater Geraldton

LOCAL GOVERNMENT AREA IN WESTERN AUSTRALIA

Greater Geraldton

The City of Greater Geraldton is a local government area in the Mid West region of Western Australia, north of the state capital, Perth on the Indian Ocean. It covers an area of , and its seat of government is the town of Geraldton.

https://en.wikipedia.org/wiki/City_of_Greater_Geraldton

Greater administrative area

1946–1954 ADMINISTRATIVE DIVISIONS OF CHINA

Great Administrative Area; Great administrative area; Greater Administrative Area; Greater administrative area; Greater Administrative Region

Greater administrative areas () were early top-level administrative divisions of the People's Republic of China that directly governed provinces and municipalities. These were the largest-ever political divisions of China and were controlled by the Central People's Government.

https://en.wikipedia.org/wiki/Greater_administrative_area

Wikipedia

Stochastically stable equilibrium

In game theory, a stochastically stable equilibrium is a refinement of the evolutionarily stable state in evolutionary game theory, proposed by Dean Foster and Peyton Young. An evolutionary stable state S is also stochastically stable if under vanishing noise, the probability that the population is in the vicinity of state S does not go to zero.

The concept is extensively used in models of learning in populations, where "noise" is used to model experimentation or replacement of unsuccessful players with new players (random mutation). Over time, as the need for experimentation dies down or the population becomes stable, the population will converge towards a subset of evolutionarily stable states. Foster and Young have shown that this subset is the set of states with the highest potential.

https://en.wikipedia.org/wiki/Stochastically stable equilibrium