Behavior Trees (BTs) were invented as a tool to enable modular AI in computer games, but have received an increasing amount of attention in the robotics community in the last decade. With rising demands on agent AI complexity, game programmers found that the Finite State Machines (FSM) that they used scaled poorly and were difficult to extend, adapt and reuse.
Sorption
fixed-bed column experiments were performed using a titanium
phosphate ion-exchanger composed of −H2PO4 units [TiO(OH)(H2PO4)·H2O].
Model mine water containing five divalent metal ions (Cu2+, Zn2+, Mn2+, Ni2+, and Co2+) and a few closed-mine water samples were treated to evaluate the
sorption preference of the material. For the first time, dynamic ion-exchange
capacities (estimated to be between 3.2 and 4.2 mequiv g–1) and static ion-exchange uptakes (calculated to be between 3.1 and
3.5 mequiv g–1) were obtained for the same TiP1
sorbent and data were discussed in terms of sorption behavior. It
was found that sorption processes on TiP1 in model and closed-mine
waters during a column experiment could be accurately predicted from
the corresponding batch experiment (including the sorbent’s
capacities in different types of waters). A competitive sorption phenomenon
in favor of Cu2+ on TiP1 was established for all cases,
pointing toward the possibility of isolating pure copper concentrate
from closed-mine waters. The relatively high amounts of calcium and
magnesium ions present in mine waters did not appear to considerably
affect the selectivity of TiP1 material. Exploratory experiments for
sorbent regeneration and desorption using a low concentration of nitric
acid were demonstrated.
In this paper, we show how classical tactical formation patterns and flanking strategies, such as the line formation and the enveloping maneuver, can be seen as the result of maximizing a natural formation utility.The problem of automatic formation keeping is extremely well studied within the areas of control and robotics, but the reasons for choosing a particular formation shape and position is much less so.By analyzing a situation with two adversarial teams of agents facing each other, we show that natural assumptions regarding the target selection of the agents and decreasing weapon efficiency over distance, can be used to optimize a measure of utility over agent positions. This optimization in turn results in formations and positions that are very similar to the ones being used in practice. We present both analytical results for simple examples as well as numerical results for more complex situations.
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