人工知能学会
経営課題にAIを！ビジネスインフォマティクス研究会 (第7回)
JSAI Special Interest Group on Business Informatics (SIG-BI #7)

ὶධࡍࡿఫẸࡢᒓᛶ࡜ᆅ༊ࡢ❧ᆅ⎔ቃࢆ㋃ࡲ࠼ࡓேཱྀືែ
ࢩ࣑࣮ࣗࣞࢩࣙࣥSimulation of population dynamics based on the attributes of the inhabitants and thelocation of the district
㟷ᮌົ1

಴ᶫ

⠇ஓ 1

Tsutomu Aoki1, Setsuya Kurahashi111⟃Ἴ኱ᏛUniversity of Tsukuba

Abstract: The Japanese cities face problems such as a declining population in rural areas or a lack ofnursery schools in urban areas. To solve these problems, it is important to make policies based on estimationof population. This paper proposes a short-term estimation method of the population by Agent Based
Simulation(ABS). To estimate expansion of residential areas in a city, this model is based on inhabitants’autonomous decision making to move with simple rules. The proposed method uses Mesh-based Population
Census Data and other locational data to understand a population distribution in a city and we try toconstruct a model for citizens and public servants working in the city planning department.

1ࡣࡌࡵ࡟

1.1 ┠ⓗᮏ◊✲ࡢ┠ⓗࡣࠊ㒔ᕷ㑹እࡢேཱྀࡀὶධࡍࡿᆅ༊ࡢேཱྀືែࢆ࢚࣮ࢪ࢙ࣥࢺ࣮࣋ࢫࢩ࣑࣮ࣗࣞࢩࣙࣥ㸦ABS㸧࡟ࡼࡾ⾲⌧ࡋࠊ✵㛫ࢆ㋃ࡲ࠼ࡓ▷ᮇⓗ࡞ேཱྀືែࢆண ࡍࡿᡭἲࢆᥦ᱌ࡍࡿࡇ࡜࡛࠶ࡿࠋࣔࢹ࡛ࣝࡣࠊὶධேཱྀ࡟↔Ⅼࢆ⤠ࡾࠊGIS ࡟ࡼࡿ❧ᆅ⎔ቃ㸦㒔ᚰ࡬ࡢ࢔ࢡࢭࢫࠊᆅ౯ࠊேཱྀศᕸ㸧ࢆ࣓ࢵࢩࣗ༢఩࡛ࣔࢹࣝ࡟཯ᫎࡉࡏࠊᒃఫᆅ㑅ᢥ࡟࠾ࡅࡿ⾜ືࣔࢹࣝࢆྛ࢚࣮ࢪ࢙ࣥࢺ㸦㌿ධ⪅㸧࡟⤌ࡳ㎸ࡳࠊ࣑ࢡࣟ࡞ேཱྀືែࢆ⾲⌧ࡍࡿࠋලయⓗ࡟࡝ࡢࡃࡽ࠸ࡢ࣮࣌ࢫ࡛ேཱྀࡀቑຍࡋࠊ࿘㎶ࡢ⾤୪ࡳࡀኚ໬ࡍࡿ࠿ࡣࠊ஦ᚋⓗ࡟ࡋ࠿ᢕᥱ࡛ࡁ࡚࠸࡞࠸࡜࠸࠺ㄢ㢟ࡀ࠶ࡿࠋࡲࡓࠊ⮬἞య࡛ࡣ㛗ᮇィ⏬࡟ᇶ࡙ࡁᑠ୰Ꮫᰯࡢ⤫ᗫྜࢆ㐍ࡵࡿ୰࡛ࠊ▷ᮇⓗ࡟ಖ⫱ᅬࡀᚲせ࡞≧ἣࡀ⏕ࡌࡓሙྜࠊィ⏬࡜⌧ᐇ࡜ࡢᩚྜᛶࡀၥࢃࢀ࡚ࡋࡲ࠺≧ἣࡶ⪃࠼ࡽࢀࡿࠋ2ඛ⾜◊✲2.1 ேཱྀືែ࡟㛵ࡍࡿ◊✲ࡢ࢔ࣉ࣮ࣟࢳேཱྀືែ࡟㛵ࡍࡿ◊✲࡟ࡣࠊㄪᰝ࣭ศᯒ◊✲ࠊᩘ⌮ࣔࢹࣝࠊࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⏝࠸ࡓ◊✲ࡀ࠶ࡿࠋㄪᰝ࣭ศᯒ◊✲࡟࠾࠸࡚ࠊ㛗἟ 2) ࡣࠊ஦౛◊✲࡜
1.2 ⫼ᬒࡋ࡚㒔ᚰᒃఫ⪅ࡢᒓᛶ࡜ᒃఫᆅ㑅ᢥࡢ࣓࢝ࢽࢬ࣒ࢆㄪᰝࡋࠊ⚟ᒸᕷෆࡢ⸆㝔ᆅ༊࡟࠾࠸࡚඲ᩘ࡟࠶ࡓࡿᆅ᪉࡛ࡣேཱྀῶᑡ♫఍ࢆ㏄࠼ࡿ୰ࠊ㒔ᚰ࡛ࡣᚅᶵ
10,605 ௳㸦ᅇ཰ᩘ 893 ௳㸧ࡢ㒑㏦ㄪᰝ࠿ࡽࠊྠᆅ༊ඣ❺ࡢၥ㢟ࡀⓎ⏕ࡍࡿ➼ࠊேཱྀࡢኚ໬ࢆⓗ☜࡟ᤊ࠼ࡓᨻ⟇ࡢ㔜せᛶࡀ㧗ࡲࡗ࡚࠸ࡿࠋከࡃࡢ⮬἞య࡛ࡣࠊ ࡢᒃఫ⪅ࡣศㆡ࣭㈤㈚ࢆၥࢃࡎከࡃࡀᕷእฟ㌟⪅࡛ࠊศㆡᒃఫ⪅ࡣ୍ᗘᕷෆ࡟㌿ධࡋࡓᚋ࡟⌧ఫᆅ࡬⛣ࡗ
3 ᖺ㹼10 ᖺ⛬ᗘ࡟ࢃࡓࡿ⾜ᨻィ⏬࡟ᇶ࡙ࡁࠊ஦ᴗࡸ࡚࠸ࡓࡇ࡜ࡸᐃఫࡋ࡚࠸ࡓࡇ࡜ࢆ᫂ࡽ࠿࡟ࡋࠊ㒔ᚰ᪋タ⟶⌮➼࡟ྲྀࡾ⤌ࡴࡀࠊࡑࢀࡽࡢィ⏬ࡣ୍⯡࡟ࢥᒃఫࢆ㑅ᢥࡍࡿ㝿࡟ᕷෆࡢࡉࡲࡊࡲ࡞ఫᏯᆅࡀೃ⿵࣮࣮࣍ࢺせᅉἲࡸከᆅᇦࣔࢹࣝ࡟ࡼࡿᑗ᮶ேཱྀ᥎ィ࡜࡞ࡾᚓࡿࡇ࡜࡜㒔ᚰᒃఫࢆ㑅ᢥࡍࡿ㝿࡟ࡣࠊ฼౽࡟ᇶ࡙ࡃ㟂せࡢண ࡀ⾜ࢃࢀࡿࠋࡇࢀࡽࡢ᥎ィࡣࠊᛶࡢ㧗ࡉࡀࡑࡢせᅉ࡟࡞ࡿࡇ࡜ࢆศᯒࡋ࡚࠸ࡿࠋ⤫ィⓗᡭἲ࡛࠶ࡾࠊỗ⏝ᛶࡣ㧗࠸ࡀእⓗせᅉ࡟ࡼࡗᩘ⌮ࣔࢹ࡛ࣝࡣࠊேཱྀࡢቑῶࢆ୰す 3) ࡀ GIS ࡢᢏ࡚ᑗ᮶ேཱྀࡀ࡝ࡢࡼ࠺࡟ኚ໬ࡍࡿ࠿࡜࠸ࡗࡓศᯒ࡟ࡣ୙ྥࡁ࡛࠶ࡿ 1) ࠋᆅᇦࡢேࡓࡕࡀ኱つᶍ࣐ࣥࢩࣙ⾡ࢆ⏝࠸࡚࣓ࢵࢩࣗ༢఩㸦1km×1km㸧࡛ࢥ࣮࣮࣍ࢺࣥࡢᘓタணᐃᆅ࡜᏶ᡂ᫬ᮇࢆㄆ㆑ࡋ࡚࠸ࡓ࡜ࡋ࡚ࡶࠊ ኚ໬⋡ἲ࡟ࡼࡿᑗ᮶ேཱྀ᥎ィࢆ⾜࠸ࠊ㒔ᕷᵓ㐀ࢆྍ人工知能学会
経営課題にAIを！ビジネスインフォマティクス研究会 (第7回)
JSAI Special Interest Group on Business Informatics (SIG-BI #7)

ど໬ࡍࡿࡇ࡜࡛ࠊࡉ࠸ࡓࡲᕷࡢᑗ᮶ࡢ㧗㱋໬⋡ࡀᕷෆ࡛ࡶ኱ࡁࡃ␗࡞ࡿࡇ࡜➼ࢆ♧ࡋࡓࠋࢩ࣑࣮ࣗࣞࢩࣙࣥ࡟ࡼࡿศᯒ࡛ࡣࠊABS ࢆ⏝࠸࡚㒔ᕷࡢࢫࣉ࣮ࣟࣝ໬ࢆࢩࣥࣉࣝ࡞⾜ືࣔࢹࣝ࡟ࡼࡾ⾲⌧ࡋࡓ Felsen4) ࡢ Sprawl Effect ࣔࢹࣝࡀ࠶ࡿࠋࣔࢹ࡛ࣝࡣ࢚࣮ࢪ࢙ࣥࢺ࡟ࠕᒃఫᆅ᥈⣴⪅ࠖ࡜ࠕᐙࠖࡢ 2 ࡘࡢ≧ែࢆ௜୚ࡋࠊ࢚࣮ࢪ࢙ࣥࢺࡣࡲࡎࠕᒃఫ
ᆅ᥈⣴⪅ࠖ࡜ࡋ࡚㨩ຊⓗ࡞ᅵᆅࢆ᥈ࡋ࡚⛣ືࡋࠊᒃఫᚋࡣࠕᐙࠖࡢ≧ែ࡜࡞ࡿࠋࠕᐙࠖࡀ࠶ࡿ࡜ࡑࡢᆅᇦࡣᩚഛࡉࢀᚎࠎ࡟ᅵᆅࡢ㨩ຊࡀୖࡀࡾࠊ௚ࡢࠕᒃఫᆅ᥈⣴⪅ࠖ࡜࡞ࡗࡓ࢚࣮ࢪ࢙ࣥࢺࡶ㞟ࡲࡿࡀࠊ㐣ᐦ࡟࡞ࡿ࡜ᅵᆅࡢ㨩ຊᗘࡣᾘ⁛ࡋࠊ࢚࣮ࢪ࢙ࣥࢺࡣ෌ࡧ⛣ືࢆ⧞ࡾ㏉ࡍ࡜࠸࠺ࣔࢹ࡛ࣝࠊ㒔ᕷࡢࢫࣉ࣮ࣟ
ࣝ໬ࢆືⓗ࡟♧ࡋࡓࠋ⚟⏣ 5) ࡣබⓗ⤫ィࢹ࣮ࢱ࠿ࡽ
ABS ࡢ࢚࣮ࢪ࢙ࣥࢺ࡟㒔ᕷఫẸࡢᒓᛶࢆ᚟ඖࡍࡿᡭἲ࡜ࡋ࡚ SA ἲࢆ⏝࠸ࡓྛ௬᝿♫఍ࢆᵓ⠏ࡋࠊࢩ࣑࣮ࣗࣞࢩࣙࣥ࡟ࡼࡾேཱྀ᥎ィࢆ⾜ࡗ࡚ᚑ᮶ࡢᡭἲ࡜ࡢẚ㍑࡛ጇᙜ࡞᥎ィ⤖ᯝࢆᚓ࡚࠸ࡿࠋᒣ⏣ 1) ࡣࠊ㒔ᕷఫẸࢆ࢚࣮ࢪ࢙ࣥࢺ࡜ࡋࠊ࣑ࢡࣟ࡞ୡᖏࡢኚ໬࡜㒔ᕷ㛫ࡢ⮬ᚊⓗ࡞㌿ᒃ⾜Ⅽࡢ⤖ᯝ࠿ࡽࠊ」ᩘࡢᕷ༊⏫ᮧࡀ㞄᥋ࡍࡿ㑹እᆅᇦࡢ࣐ࢡࣟ࡞ேཱྀືែࢆ⾲⌧ࡋࠊᕷ༊⏫ᮧ༢఩࡛ࡢᨻ⟇ࡀᑗ᮶ேཱྀ࡟୚࠼ࡿᙳ㡪ࢆศᯒ࡛ࡁࡿᡭἲࢆᥦ᱌ࡋ࡚࠸ࡿࠋ

2.2 ◊✲ࡢ఩⨨࡙ࡅᮏ◊✲ࡢㄢ㢟࡜ࡍࡿ▷ᮇⓗ࠿ࡘᒃᡤⓗ࡞ேཱྀືែࡢண ࡣࠊඛ⾜◊✲ࢆ㋃ࡲ࠼ࡘࡘ᪂ࡓ࡞࢔ࣉ࣮ࣟࢳࢆᵓ⠏ࡍࡿᚲせࡀ࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋᮏ◊✲ࡢ┠ᶆࡣࠊ౛࠼ࡤᅗ 1 ࡢࡼ࠺࡞ேཱྀቑຍࡀ㉳ࡁ࡚࠸ࡿᆅ༊࡟࠾ࡅࡿேཱྀศᕸࡢኚ໬ࢆࠊ㛗ᮇࡢᑗ᮶ேཱྀ᥎ィ࡟⦡ࡽࢀࡎ࡟ࠊ㏲ḟⓗ࡟ண ࡍࡿࣔࢹ࡛ࣝ࠶ࡿࠋ

ᅗ 1㸸A ᕷࡢᖹᡂ 27 ᖺ㹼ᖹᡂ 22 ᖺேཱྀቑῶ3◊✲ࡢ㐍ࡵ᪉

3.1 ࢔࢘ࢺࣛ࢖ࣥ
ᥦ᱌ࡍࡿேཱྀືែࢆண ࡍࡿᯟ⤌ࡳࡣࠊࡇࢀࡲ࡛
ࡢඛ⾜◊✲ࡢᡂᯝࢆά⏝ࡍࡿࠋㄪᰝ࣭ศᯒ◊✲ࡢ▱ぢ࡛ࡣࠊศㆡ࣐ࣥࢩࣙࣥࡢ㉎ධᒙࡣ㒔ᕷࡢ฼౽ᛶ࡞࡝ࢆ⪃៖ࡋ࡚ᒃఫᆅࢆ㑅ᢥࡋࠊᇶᮏⓗ࡟ᐃఫࡋ࡚࠸
ࡿࡇ࡜࠿ࡽࠊ⾜ືࡢࣔࢹࣝ໬ࡀྍ⬟ࡔ࡜᥎ ࡉࢀࡿࠋࡲࡓࠊὶධேཱྀࡢண ࢆࠊᣢࡕᐙࢆ㉎ධࡍࡿᒓᛶ㸦30
㹼40 ṓྎ㸧࡟⤠ࢀࡤࠊࢩࣥࣉࣝ࡞ࣔࢹ࡛ࣝࡶ⾲⌧࡛ࡁࡿ࡜⪃࠼ࡽࢀࡿࠋᩘ⌮ࣔࢹ࡛ࣝ♧ࡉࢀࡓ࣓ࢵࢩࣗ
༢఩࡟ࡼࡿேཱྀືែࡢศᯒࡣࠊኚ໬ࡢྍど໬࡜✵㛫ࡢ≉ᚩࢆ⾲⌧ࡍࡿࡢ࡟᭷ຠ࡞ᡭẁ࡛࠶ࡾࠊࢩ࣑ࣗࣞ
࣮ࢩࣙࣥ࡜ほ ࢹ࣮ࢱࡢᶫΏࡋ࡜ࡋ࡚ࡶά⏝࡛ࡁࡿࠋࢩ࣑࣮ࣗࣞࢩࣙࣥࡢᡭἲ࠿ࡽࡣࠊ࢚࣮ࢪ࢙ࣥࢺ࡟⮬ᚊⓗ࡞ᒃఫᆅ㑅ᢥࢆࡉࡏࡿࡇ࡜࡛ࠊᒃఫ࢚ࣜ࢔ࡢࢫ
ࣉ࣮ࣟࣝ໬࡜⎔ቃࡢኚ໬ࢆືⓗ࡟⾲⌧࡛ࡁࡿࠋࡲࡓࠊࣔࢹࣝࡢᵓ⠏࡟ࡼࡾ⌧ᐇࡢேཱྀືែ࡟㏆ఝࡉࡏࡿࡇ
࡜ࡀྍ⬟࡛࠶ࡿࡇ࡜ࡶࡍ࡛࡟♧ࡉࢀ࡚࠸ࡿࠋ௨ୖࡢ
ࡇ࡜࠿ࡽࠊᮏ◊✲࡛ࡣ ABS ࢆ⏝࠸࡚ࠊ࣓ࢵࢩࣗ༢఩
࡟ࡼࡿேཱྀືែࢆண ࡍࡿᡭἲࢆᥦ᱌ࡍࡿࠋࡇࢀ࡟
ࡼࡾࠊᚑ᮶ࡢேཱྀ᥎ィࡀᢅࢃ࡞࠸้ࠎ࡜ኚ໬ࡍࡿே
ཱྀືែࢆ⾜ືࣔࢹࣝ࡜✵㛫᝟ሗ࡛㏆ఝࡉࡏࠊᵝࠎ࡞ࢩࢼࣜ࢜ศᯒࢆ⾜࠺ࡇ࡜ࡀྍ⬟࡟࡞ࡿ࡜⪃࠼ࡽࢀࡿࠋ
ࡑࡢ⤖ᯝࠊ౛࠼ࡤ 10 ᖺᚋ࡟⪁ே᪋タ࡜ࡋ࡚⏝࠸ࡿᘓ≀ࢆࠊ▷ᮇⓗ࡟ࡣಖ⫱ᅬ࡜ࡋ࡚౑࠼ࡿࡼ࠺ᩚഛࡍࡿ
࡜࠸࠺ࡼ࠺࡞ᨻ⟇❧᱌࡟ᐤ୚ࡍࡿࡇ࡜ࡀᮇᚅ࡛ࡁࡿࠋᮏ◊✲ࡢ࢔࢘ࢺࣛ࢖ࣥࢆࠊᅗ 2 ࡟♧ࡍࠋᅗ 2㸸◊✲ࡢ࢔࢘ࢺࣛ࢖ࣥᮏ◊✲ࡣࠊFelsen ࡢ⾜ືࣔࢹࣝࢆᇶᮏⓗ࡞௬ㄝ࡜ࡋࠊᐇ㝿ࡢ✵㛫࡬㐺⏝ࡋ࡚ேཱྀືែࡢண ࢆヨࡳࡿࠋලయⓗ࡟ࡣࠊ(1)࡛ ABS ࡢ⎔ቃࢆタᐃࡋࠊ(2)࡛ேཱྀ
ὶධᆅ༊ࡢேཱྀືែࡢࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⾜࠺ࠋ人工知能学会
経営課題にAIを！ビジネスインフォマティクス研究会 (第7回)
JSAI Special Interest Group on Business Informatics (SIG-BI #7)

3.2 ࢩ࣑࣮ࣗࣞࢩࣙࣥࡢࢫࢸࢵࣉࢩ࣑࣮ࣗࣞࢩࣙࣥࡢࢫࢸࢵࣉ᱌ࢆᅗ 3 ࡟♧ࡍࠋᅗ 3㸸ࢩ࣑࣮ࣗࣞࢩࣙࣥࡢࢫࢸࢵࣉ㸦࢖࣓࣮ࢪ㸧⾜ືࣔࢹ࡛ࣝࡣࠊ㨩ຊᗘࡀ㧗࠸࡜ࡇࢁࢆồࡵ࢚࣮ࢪ࢙ࣥࢺࡀ⛣ື࡜ᒃఫࢆ⧞ࡾ㏉ࡍࠋ(1)࡛ࡣࠊࡑࡢ㨩ຊᗘ㸦‫ܣ‬௜௝ 㸧ࢆ࣓ࢵࢩࣗ༢఩࡛タᐃࡍࡿࡓࡵࠊḟࡢᚓⅬ໬ࢆ⾜࠺ࠋ‫ܣ‬௜௝ = ‫ܦ‬௜௝ + ‫ܮ‬௜௝ + ܲ௜௝‫ܣ‬௜௝ : ࣓ࢵࢩࣗ(i , j)ࡢ㨩ຊᗘ Attraction‫ܦ‬௜௝ : ࣓ࢵࢩࣗ(i , j)ࡢ᭱ᐤࡾ㥐ࡲ࡛ࡢ㊥㞳ᚓⅬ Distance‫ܮ‬௜௝ : ࣓ࢵࢩࣗ(i , j)ࡢᆅ౯ᚓⅬ Landܲ௜௝ : ࣓ࢵࢩࣗ(i , j)ࡢேཱྀᚓⅬ Population‫ܦ‬௜௝ ࡣࠊ᭱ᐤࡾ㥐ࡲ࡛ࡢ㊥㞳࡛࠶ࡿࠋ࢚ࣜ࢔඲య࡟࠾ࡅࡿᶆ‽໬ᚓⅬࢆồࡵࠊ㊥㞳ࡀ▷࠸࡯࡝㨩ຊᗘࡀ㧗ࡃ࡞ࡿࡼ࠺࡟ࡍࡿࠋ‫ܮ‬௜௝ ཬࡧܲ௜௝ ࡶྠᵝ࡟ࠊࡑࢀࡒࢀᆅ౯࡜ேཱྀࡢᶆ‽໬ᚓⅬࢆồࡵࠊྜィⅬࡀ㧗࠸࡯࡝㨩ຊ࡞ᅵᆅ࡟࡞ࡿࡼ࠺࣓ࢵࢩࣗࢆタᐃࡍࡿࠋࡲࡓࠊேཱྀࡢቑ࠼ࡿవᆅࡢ࡞࠸࣓ࢵࢩࣗ࡟ࡘ࠸࡚ࡣࠊ࢚࣮ࢪ࢙ࣥࢺࡀධࡽ࡞࠸ࡼ࠺࡟タᐃࡍࡿࠋ(2)࡛ࡣࠊ(1)ࡢ⎔ቃࡢࡶ࡜࡛ࠊFelsen ࡢ⾜ືࣔࢹࣝࢆ㐺⏝ࡍࡿࠋศᒱࡣᅗ 4 ࡢὶࢀ࡟ᚑ࠺ࠋࢩ࣑࣮ࣗࣞ
ࢩࣙࣥࡢᅇᩘࡣᐇ㝿ࡢࢹ࣮ࢱ࡜ẚ㍑ࡋࡓୖ࡛ࠊ⌧ᐇࡢ᫬㛫㍈࡟㏆ఝࡉࡏࡿࠋABS ࡟ࡼࡾᚓࡽࢀࡿࡢࡣ 2ࡘࡢ᥎ᐃศᕸ࡛ࠊ1 ࡘ┠ࡣࠊ࢚࣮ࢪ࢙ࣥࢺࡀ⛣ࡾఫࡴࡇ࡜࡛ኚ໬ࡋࡓᑐ㇟ᆅ༊ࡢ㨩ຊᗘࡢศᕸ࡛ࠊḟᮇࡢᒃఫ࢚ࣜ࢔ࡢᣑ኱ࡀ♧ࡉࢀࡿࠋ2 ࡘ┠ࡣࠊ࢚࣮ࢪ࢙ࣥ
ࢺࡢேཱྀᐦᗘࡢศᕸ࡛ࠊὶධேཱྀࢆ๭ࡾᙜ࡚ࡿࡇ࡜࡛ḟᮇࡢேཱྀண ศᕸ࡜࡞ࡿࠋ2 ࡘࡢ᥎ᐃศᕸࡣࣉࣟࢢ࣒ࣛ 6) ࡟ࡼࡾ࣓ࢵࢩࣗ༢఩࡛ᩘ್໬ࡍࡿࠋ

ᅗ 4㸸⾜ືࣔࢹࣝࡢศᒱ

3.3 ࢹ࣮ࢱᅜࡢබ⾲⤫ィࢹ࣮ࢱࢆά⏝ࡍࡿࠋGIS ࡢ࣓ࢵࢩࣗ
ࢹ࣮ࢱࡣ⊂❧⾜ᨻἲே⤫ィࢭࣥࢱ࣮ࡢ JSTAT MAPࢩࢫࢸ࣒➼ࢆά⏝ࡍࡿࠋ

3.4 ホ౯᪉ἲ
ศᯒᡭἲࢆࡉࡲࡊࡲ࡞ᆅᇦ࡟㐺⏝ࡋࠊேཱྀືែࢆⓗ☜࡟⾲⌧࡛ࡁ࡚࠸ࡿࡢ࠿ࢆ᳨ドࡍࡿࠋ4௒ᚋࡢྲྀ⤌ࡳ௒ᚋࡣࠊ࢔࢘ࢺࣛ࢖ࣥ࡟ἢࡗ࡚ࣔࢹࣝࢆᐇ⿦ࡋࠊ
ேཱྀືែࢆண ࡍࡿࠋᐇ㦂⤖ᯝࢆࡶ࡜࡟ண ࡢ⢭ᗘࢆ㧗ࡵࡿࡓࡵࠊࢩ࣑࣮ࣗࣞࢩࣙࣥࡸ࢔ࣉ࣮ࣟࢳࢆᨵၿࡋ࡚࠸ࡃ⪃࠼࡛࠶ࡿࠋ≉࡟ࢩ࣑࣮ࣗࣞࢩࣙࣥࡢ᫬
㛫㍈࡜⌧ᐇ࡜ࡢ㏆ఝ࡟ࡘ࠸࡚ࡣࠊࣔࢹࣝࡢㄢ㢟࡜ㄆ㆑ࡋ࡚࠾ࡾࠊࢹ࣮ࢱྠ໬ࡢᡭἲࢆ᳨ウࡍࡿࠋࢹ࣮ࢱ
ྠ໬࡟ࡼࡾࠊࣔࢹࣝࡢ᭦᪂࡜ண ࡢᨵၿࡀᮇᚅ࡛ࡁࡿࡓࡵࠊᮏ◊✲ࡢ㔜せ࡞◊✲ㄢ㢟࡜ࡋ࡚ྲྀࡾ⤌ࡴ⪃࠼࡛࠶ࡿࠋཧ⪃ᩥ⊩[㸯] ᒣ⏣カᖹ, ฟཱྀᘯ: ⮬ᚊⓗ࡞㌿ᒃࢆ⪃៖ࡋࡓ኱㒔ᕷ㑹እࡢேཱྀືែࢩ࣑࣮ࣗࣞࢩࣙࣥ, ィ ⮬ືไᚚᏛ఍ㄽᩥ㞟, vol. 52, no. 10, p. 555-565,(2016)

人工知能学会
経営課題にAIを！ビジネスインフォマティクス研究会 (第7回)
JSAI Special Interest Group on Business Informatics (SIG-BI #7)[㸰] 㛗἟బᯞ, Ⲩ஭Ⰻ㞝: 㒔ᚰᒃఫ⪅ࡢᒓᛶ࡜ᒃఫᆅ㑅ᢥࡢ࣓࢝ࢽࢬ࣒, ᆅᏛ㞧ㄅ, vol. 119, no. 5, p.
794-809, (2010)[㸱] ୰す㈼ஓ, ᑠᆏ▱⩏, ㉥ᫍ೺ኴ㑻, ▼஭൤ග,ᓊ஭㝯ᖾ: ࣓ࢵࢩࣗ༢఩ࡢᑗ᮶ேཱྀ᥎ィᡭἲࢆ⏝࠸ࡓ㒔ᕷᵓ㐀ࡢྍど໬࡟㛵ࡍࡿ◊✲, 㒔ᕷィ⏬ㄽᩥ㞟, vol. 46, no. 3, p. 445-450, (2011)[㸲] Felsen M., Wilensky U.: NetLogo Urban Suite-Sprawl
Effect model, Center for Connected Learning andComputer-Based Modeling, Northwestern University,
Evanston, IL, (2007)[㸳] ⚟⏣ ⣧ஓ, ႐ከ ୍: ࢚࣮ࢪ࢙ࣥࢺ࣮࣋ࢫࡢேཱྀ᥎ィࣔࢹࣝ࡟࠾ࡅࡿᒓᛶỴᐃᡭἲࡢホ౯, ࢩࢫࢸ࣒ไᚚ᝟ሗᏛ఍ㄽᩥㄅ, vol. 27, no. 7, p. 279289, (2014)[㸴] Thiele Jan C.: R Marries NetLogo Introduction to theRNetLogo Package, Journal of Statistical Software,
vol. 58, no. i02, (2014)