A very general analytic term for this is the "horizon effect" or "horizon problem".
Wikipedia does a decent job explaining the origins and use of the term, so I'll go ahead and quote it -
The horizon effect, also known as the horizon problem, is a problem in artificial intelligence where, in many games, the number of possible states or positions is immense and computers can only feasibly search a small portion of it, typically a few plies down the game tree. Thus, for a computer searching only five plies, there is a possibility that it will make a detrimental move, but the effect is not visible because the computer does not search to the depth of the error (i.e. beyond its "horizon").
When evaluating a large game tree using techniques such as minimax
with alpha-beta pruning, search depth is limited for feasibility
reasons. However, evaluating a partial tree may give a misleading
result. When a significant change exists just over the horizon of the
search depth, the computational device falls victim to the horizon
Hans Berliner named this phenomenon in 1973, "The Horizon Effect",
which he and other researchers had observed. He split the effect into
two, the Negative Horizon Effect is when it "results in creating
diversions which ineffectively delay an unavoidable consequence or
make an unachievable one appear achievable." For the "largely
overlooked" Positive Horizon Effect, "the program grabs much too soon
at a consequence that can be imposed on an opponent at leisure,
frequently in a more effective form."
The term is now applied freely to matters where the horizon takes very different forms than in the original use. It this case, the horizon may be time scales, where the full accounting of the effects over time is not realized. Or it may be spacial, where the full span of the effected area is not taken into account. Or it may be due to a non-egalitarian approach to weighting values which causes the score to change depending on your perspective. Often, the closer you are to some local optima, the less likely you are to find the global optimum.
CEO Horizon, Optimal Pay Duration and the Escalation of Short-Termism∗
Ivan Marinovic† Felipe Varas‡, June 12, 2017
studies optimal CEO contracts when managers can manipulate their
performance measure, sometimes at the expense of firm value. Optimal
contracts defer compensation. The manager’s incentives vest over time
at an increasing rate and compensation becomes increasingly sensitive
to short-term performance. This process generates an endogenous CEO
horizon problem whereby managers intensify performance manipulation in
the final years in office. Contracts are designed to foster effort
while minimizing the adverse effects of manipulation. We characterize
the optimal mix of short and long-term compensation along the
manager’s tenure, the optimal vesting period of incentive pay, and the
resulting dynamics of managerial short-termism over the CEO’s tenure.
While this example happens to involve an exploitative situation (it's based on the assumption that the manager will exploit the situation), It's intended to show the free use of the term outside of game algorithms in ordinary writing.
Another technical, model related paper, but far distant from the game engine origin.
The investment horizon problem: A resolution
Knut K. Aase ∗
In the canonical model of investments, the optimal fractions in
the risky assets do not depend on the time horizon. This is against
empirical evidence, and against the typical recommendations of portfolio managers. We demonstrate that if the intertemporal coefficient
of relative risk aversion is allowed to depend on time, or the age of
the investor, the investment horizon problem can be resolved.
finally, a very generic and relevant example.
Horizon Effects, Sustainability, Education and Ethics: Toward an Economics of
Frederic B. Jennings, Jr., Ph.D. 22 June 2007
Abstract: Horizon Effects, Sustainability, Education and Ethics
The core of an ecological economics is interdependence: substitution
complementarity. Yet orthodox economics stands on substitution
assumptions as the universal human relation. A theory so founded does
not apply to a complementary realm. The optimal organizational form in
a world of substitution is competition among our resources. Where
complementarity rules, however, this is precisely wrong: cooperation
is sought instead. Interdependence is also the basis for bounded
rationality theories. If consequences sweep outward forever, our
prior anticipation of those outcomes shall be contained. The range of
our understanding – called the planning horizon in choice – sets
the boundedness of our rationality into an ordinal frame. Especially
in the presence of complementarity, impacts grow as they spread,
displacing competition for cooperation as our welfare ideal. Examples
are found in ecology, education and ethical culture: none are well
served by competition. The health of ecology lies in complementarities
sundered by competition. The educational system in its intangible
information may be our clearest case of complementarity: it is a good
illustration of failure. The ethical manifestation of this problem is
short horizons, a culture ruled by myopic concerns. Such conclusions
are framed within a horizonal theory of foresight, to be explained
below. Prices, economic growth and most of our ecological losses are
tied to planning horizons, which extend through learning and trust.
Longer planning horizons transform substitutes into complements, a
shift of interdependence calling for institutional change. Without
adapting incentives to cooperation, progress is slowed: horizon
effects show why. A horizonal economics of complementarity is
introduced and discussed. KEYWORDS interdependence, complementarity,
cooperation, planning horizon, conscience, ecology, economics,
education, ethics 1 This paper was presented at the INFER 2006
Workshop on “Bounded Rationality in Economics and Finance” in
Loughborough, Englan d.